No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Fuzzy control of self-balancing robots: A control laboratory project
Abstract and Figures
This paper presents a novel control laboratory project that provides hands‐on experience in feedback control concepts (embedded control systems) through dedicated assignments, with a particular focus on the design and implementation of fuzzy control. The project is structured around an inexpensive, portable self‐balancing robot (SBR), whose embedded system is realized using commercially available breakout boards as the first assignment. For the stabilization of the plant, students are guided to execute the essential stages of control system design, from system modeling and parameter optimization, over basic or advanced control strategy design in the MATLAB/Simulink environment, to both implementation and validation of the closed loop on the real robot. To demonstrate and foster the application of fuzzy logic, the second part of the paper introduces a simple control strategy based on fuzzy logic controllers. Then, a lookup table‐based implementation technique is described for the demonstration of manual interfacing and embedded coding of fuzzy control strategies. The proposed methods are clear and straightforward; they highly foster the understanding of feedback control techniques and allow students to gain vast knowledge in the practical implementations of control systems.
Figures - uploaded by Ákos Odry
Author content
All figure content in this area was uploaded by Ákos Odry
Content may be subject to copyright.
... SBRs are the descendants of pendulum-cart systems and are characterized by advantageous electromechanical properties. In both education and research, these mechatronic systems provide wide application spectrum and are considered as important benchmark tools to verify novel control approaches [61]. The electromechanical properties, modeling and control solutions, and applications have been summarized in detail in recent works [61], [62]. ...
... In both education and research, these mechatronic systems provide wide application spectrum and are considered as important benchmark tools to verify novel control approaches [61]. The electromechanical properties, modeling and control solutions, and applications have been summarized in detail in recent works [61], [62]. Moreover, both the employed SBR system and its conventional fuzzy control approach have been presented in detail in our earlier works [63], [64], [65]; therefore, only the key information is described in the following paragraphs. ...
... The system dynamicsẋ = h (x, u) is described with an 8dimensional nonlinear state space model as [61]: ...
In stochastic computing (SC) systems numbers are represented with mean values of random binary sequences. This paper introduces a novel fuzzy inference architecture, in which the computational mechanism is based on stochastic logic (SL). First, the basic concept of SL is described, then the architecture of the SL-based fuzzy logic controller (SFLC) is built up systematically using the derived stochastic elements. The second part of the paper demonstrates the application of the proposed techniques, where the SFLC-based control performance is evaluated on a real mechatronic system. The results show that the SL-based approach provides effective and robust control performance, simple architecture and high noise tolerance. The proposed method is also benchmarked against conventional FLCs indicating that the robustness of the stochastic architecture allowed to outperform the benchmark controllers in noisy environments.
... Incorporating FPGAs in DC motor speed control offers several advantages, such as enhanced flexibility, highspeed processing capabilities, integration of multiple functions, customizability, real-time monitoring, reduced system cost, and potential energy efficiency [39,23,22,36,11,25,1,38,32,20]. ...
... In [25], the authors propose a straightforward Fuzzy Control Strategy (FCS) for Self-Balancing Robot (SBR) systems and demonstrate an implementation technique using Look-Up Tables (LUTs) for Fuzzy Logic Controllers (FLCs). This approach is specifically tailored for educational purposes. ...
In this work, we propose the design and implementation of a parallel-structured fuzzy logic controller with integral action and anti-windup. The Grey Wolf Optimization (GWO) optimization technique is used to optimize fuzzy rules, which allows for the complicated algebraic ideas of type 1 fuzzy logic algorithms to be reduced to straightforward numerical equations for FPGA target implementation. The techniques for operating a geared DC motor are optimized by the membership function structure of our controller's data propagation. Our proposed controller was implemented in Xilinx System Generator (XSG) and co-simulated on hardware and software with VIVADO and XSG tools.
... Especially, parameter identification and automatic control of servomechanisms are widely taught in undergraduate and graduate programs related to robotics, mechatronics, and electrical engineering courses, and these topics are usually complemented by laboratory experiments [39]. The parameters to be identified include the inertia and friction of the servomechanism, and the preferred control technique is the classical Proportional Integral Derivative controller [4,6,32]. Simulation studies can be useful for rapid testing and validation of the theory under consideration. ...
... Yahya et al. [47] present the control of a robotic manipulator with three servo motors, where the control algorithm is implemented in the LabVIEW software, and the NI PCI-6602 card performs data acquisition. In Odry et al. [32], the Fuzzy Logic Toolbox of MATLAB is used to control a self-balancing robot actuated by DC motors, whose parameters are estimated by the MATLAB least-squares function. Concha Sánchez et al. [10] proposed an educational platform based on a recycled robot arm with vision operated through the MATLAB/Simulink environment. ...
Topics of automatic control, parameter identification, and state estimation of a direct current (DC) motor are widely included in undergraduate and graduate engineering programs. Traditionally, theoretical classes are accompanied by simulation or experimental laboratory sessions. The simulation techniques usually do not consider essential dynamic behaviors exhibited by physical systems, such as friction and saturation. Meanwhile, the DC servomechanism, computing device, and associated software used for the experiments are usually expensive. These situations may be avoided through mobile learning by using a low‐cost and portable platform controlled by a mobile device. This article proposes a free Android application called Control and Identification Toolbox for motors (mCIT) and a low‐cost portable platform designed to perform real‐time experiments on DC servomechanisms. The portable platform comprises a mobile device with the mCIT app, a DC servomechanism, and an Arduino‐based data acquisition system. The mobile device, which can be a smartphone, performs the computational and user interface tasks. The effectiveness of the mCIT app and platform are evaluated in online, hybrid, and face‐to‐face courses. The results indicate that the proposed mobile technique improves the teaching and learning experience of automatic control and system estimation topics.
... Different methods, such as fuzzy logic, are used in such applications [5].Fuzzy controllers are one of the techniques that ensure optimal performance in DC machines. It is important to highlight that it is straightforward to construct when compared to other DC controller systems [6]- [8]. These controllers are currently among the most well-known DC machine controller systems as a result. ...
The mathematical model of an electromechanical system and the design and implementation of a fuzzy logic controller that makes use of integral action and anti-windup in a parallel structure are both discussed in this work. One of the best controllers for conditions like disturbances and saturations is the FL control. Fuzzy logic type 1 algorithms are thoroughly studied, and difficult algebraic ideas are condensed into numerical equations. Greywolf optimization (GWO) is used to improve two parameters of our proposed controller. Vivado and XSG tools were used to co-simulate our suggested controller on both software and hardware, and the fixed-point structure of our controller's data propagation optimizes the methods used to implement it. This article's first focus is on using a better optimization approach to regulate the fuzzy controller's ideal settings in order to boost output speed and precision. Second, a pipeline method put out by XSG to create fuzzy controllers as efficiently as possible. When our controller is applied to the saturated system, the responses of the system are compared. To verify the efficacy of the proposed control strategy, a thorough comparison is done using control simulations between it and previous PID systems.
... In [20], the authors suggest a simple Fuzzy Control Strategy (FCS) for Self-Balancing Robot (SBR) systems and an implementation technique using Look-Up Tables (LUTs) for (FLCs). The proposed approach is specifically designed for educational purposes. ...
This study explores an electromechanical system with saturation, where a hybrid fuzzy controller with integral action and anti-windup is implemented on an FPGA board. The research highlights the use of parallel-structured fuzzy controllers, which excel in handling disturbances and saturation. To enhance controller performance, Particle Swarm Optimization (PSO) is employed to fine-tune the membership functions and feedback loop gains. The complex type-1 fuzzy logic algorithms are converted into mathematical equations suitable for VHDL implementation. The controller design is co-simulated using Vivado and Xilinx® System Generator (XSG) tools on both software and hardware platforms, utilizing fixed point data propagation for efficient implementation. Finally, the effectiveness of the proposed controller is validated through comprehensive simulations, comparing it against traditional PID control systems.
... In [20], the authors suggest a simple Fuzzy Control Strategy (FCS) for Self-Balancing Robot (SBR) systems and an implementation technique using Look-Up Tables (LUTs) for (FLCs). The proposed approach is specifically designed for educational purposes. ...
This work explores the mathematical modeling of an electromechanical system and the design of a fuzzy logic controller that incorporates integral action and anti-windup in a parallel configuration. Fuzzy logic control (FL) is recognized as highly effective in managing disturbances and saturation conditions. Type-1 fuzzy algorithms are extensively analyzed, with complex algebraic concepts simplified into numerical equations. To optimize the proposed controller, Grey Wolf Optimization (GWO) is employed to adjust two key parameters. The controller design is co-simulated on both software and hardware platforms using Vivado and Xilinx System Generator (XSG) tools, leveraging a fixed-point structure to enhance implementation efficiency. The study has two primary objectives: first, to apply an improved optimization technique for fine-tuning the fuzzy controller's parameters to increase speed and accuracy; second, to utilize XSG's pipeline method for efficient fuzzy controller design. The controller's performance is validated by applying it to a system with saturation, comparing its responses to traditional PID systems through comprehensive simulations to demonstrate its effectiveness.
... Furthermore, to increase the robustness of the SMC and improve the transient response, the fuzzy SMC was investigated by Navabi et al. 29 Fuzzy logic control was also adopted for real flatform to investigate the effectiveness of underactuated systems, like, the BallBot. 30,31 Nevertheless, these previous publications lack an evaluation of the impact of changes in robot mass and ball size on BallBot operability. ...
The BallBot, a versatile robot system, finds applications in various domains of life. It comprises a frame moved by three wheels mounted on a ball. The robot performance is significantly influenced by its parametric configuration, including body mass, chassis size, and ball diameter. This study examines the impact of these configuration parameters on the control of the BallBot. The mathematical model of the BallBot is discussed, considering the assumptions and coordinate systems. To control the robot, a Linear Quadratic Regulator controller is designed. Subsequently, the simulation model is used to assess the effects of changing the initial parametric configuration. It is observed that altering the robot mass has a notable impact on the BallBot response, while changes in the ball diameter have a relatively insignificant effect.
... Penyesuaian parameter a, b, dan c dilakukan secara sistematis pada setiap fungsi keanggotaan, di mana pengaruh perubahan parameter ini dianalisis melalui simulasi sistem. Proses ini bertujuan untuk meningkatkan performa fuzzy logic controller dalam pengendalian robot balancing, sehingga sistem dapat merespons dengan lebih baik terhadap variasi kondisi yang dihadapi [11], [12], [13]. ...
This research develops a balancing robot control system using a fuzzy logic approach, focusing on the adjustment of membership function parameters. The main components of the system include the ESP32 microcontroller, MPU6050 sensor for detecting tilt angle and angular velocity, and L298 motor driver for DC motor actuation. Triangular-shaped membership functions are implemented, and parameters a, b, and c are adjusted through simulation to enhance system performance. Evaluation results indicate an average settling time of 1.2 seconds, a maximum overshoot of 5%, and a steady-state error of less than 2 degrees. This adjustment successfully balances response speed and stability, providing important guidance for developers in designing a more optimal fuzzy logic control system. The research was conducted at the Electrical Engineering Laboratory of 17 August 1945 University (Untag) Surabaya from June to December 2023.
... The TWSB robot is an underactuated mechanical system with high-order, multivariable, nonlinear, and tightly coupled components. As a result, numerous scientists are interested in conducting research and development on the TWSB robot [1][2][3][4][5]. ...
This paper proposes an adaptive nonlinear proportional-derivative (ANPD) controller for a two-wheeled self-balancing robot (TWSB) modeled by the Lagrange equation with external forces. The proposed control scheme is designed based on the combination of a nonlinear proportional-derivative (NPD) controller and a genetic algorithm, in which the proportional-derivative (PD) parameters are updated online based on the tracking error and the preset error threshold. In addition, the genetic algorithm is employed to adaptively select initial controller parameters, contributing to system stability and improved control accuracy. The proposed controller is basic in design yet simple to implement. The ANPD controller has the advantage of being computationally lightweight and providing high robustness against external forces. The stability of the closed-loop system is rigorously analyzed and verified using Lyapunov theory, providing theoretical assurance of its robustness. Simulations and experimental results show that the TWSB robot with the proposed ANPD controller achieves quick balance and tracks target values with very small errors, demonstrating the effectiveness and performance of the proposed controller. The proposed ANPD controller demonstrates significant improvements in balancing and tracking performance for two-wheeled self-balancing robots, which has great applicability in the field of robot control systems. This represents a promising solution for applications requiring precise and stable motion control under varying external conditions.
... Just like other generative AI, ChatGPT has certainly brought opportunities and benefits to education but also implies threats and pitfalls. 66 ...
This book presents advances in the research of educational robotics and showcases how they can be used to facilitate learning. It summarizes popular and relevant terms and theories in educational robotics via analyzing one hundred influential journal articles in this field, to provide readers background knowledge on the subject matter. This book also guides readers in understanding how different types of robotics are utilized to promote learning among different types of students, in different contexts, and in different disciplines of study.
... Just like other generative AI, ChatGPT has certainly brought opportunities and benefits to education but also implies threats and pitfalls. 66 ...
STEM is the abbreviation for the four disciplines of science, technology, engineering and mathematics. STEM education is a comprehensive education based on the idea that these four areas of learning should be taught together in an integrated manner, as opposed to teaching them separately. With this holistic learning style, students apply science, technology, engineering and mathematics in contexts that make connections between the classroom and the world around them. Thus, STEM education is an interdisciplinary approach to learning where academic concepts are coupled with real-world lessons. It also allows students to explore a wide range of topics and work with cutting-edge tools and technologies. As STEM education is viewed as a valuable method to help students better understand the world around them and gain skills such as critical thinking, problem-solving and collaboration, such education can be said to prepare students for the challenges that they will face in their future lives.
... Just like other generative AI, ChatGPT has certainly brought opportunities and benefits to education but also implies threats and pitfalls. 66 ...
Robots are becoming increasingly popular with its fast-growing intelligence due to the technology advances. Educational robots as a learning technology have great potential in many ways. However, the real requirements of educational robots are still unclear for educators and developers. Hence, this chapter aims to investigate the requirements of educational robots in all levels of education, and takes key stakeholders into consideration, namely kindergarten, primary school students, middle school students, college students, teachers as well as parents.
... Just like other generative AI, ChatGPT has certainly brought opportunities and benefits to education but also implies threats and pitfalls. 66 ...
The fourth industrial revolution keeps pushing the advancement of technology in the form of artificial intelligence (AI), robotics and natural language processing (NLP) which increasingly makes the use of conversational agents (such as chatbots) in education a possibility. Advanced conversational agents are powered by AI and exploit NLP to have text-based dialogues with users. A conversational agent can also make use of speech recognition technology to have a spoken conversation with a user. Developers of conversational agents design them to mimic human-like conversations in a way that is indistinguishable from having actual interaction with a human. As a result, some conversational agents are imbued with human qualities like personality, emotion and humor. AI-powered conversational agents are able to offer learning support and enable a learner to engage in self-assessment which can be difficult to provide in traditional learning environments. In addition to providing personalized learning to users, conversational agents adopt human pedagogical roles such as learning companions, coaches or tutors in educational settings. Pedagogic conversational agents also promote collaborative learning in technology-enhanced learning environments such as e-learning, online learning, massive open online courses (MOOC) and in other virtual worlds. The use of conversational agents as pedagogical agents is underscored as having the potential to enhance learning outcomes and memory and increase the motivation of learners to engage in the learning process. At the same time, it brings up discussions on academic integrity while applying such technology.
... Just like other generative AI, ChatGPT has certainly brought opportunities and benefits to education but also implies threats and pitfalls. 66 ...
Programming is the implementation of logic to facilitate specified computing operations and functionality which consists of traditional education (C++ and Java) and robotics. Different from robotics, traditional education has an abstract programming structure, and often students are not able to reach sufficient maturity levels without guidance. Robot-based programming is the process of defining specific commands of an application for an educational robot which is an interesting teaching tool that will help teachers when going through many topics while keeping students engaged. And moreover, it is suitable for all levels and age groups. Learning computer programming often goes along with growing other skills such as logical thinking, problem-solving through tests, modifications and optimization, problem modeling, etc. Robotics is highly stimulating for younger students and allows them to grow important soft skills such as problem-solving, creativity and team spirit. In higher education, robotics allows students to work with real hardware in order to be prepared for the challenges of real physical work. Studies have shown that the main problems of current robot-based programming feature three main points. First of all, it is impossible to promote the popularity of engineering colleges in robot-based programming because of the lack of necessary equipment. Secondly, the shortage of qualified teachers is a key factor that restricts the development of robot-based programming education. Therefore, it is necessary to improve the professional ability of front-line teachers to promote robot-based programming. Finally, related teaching materials should be used to meet the demand for students of all grades levels.
... Many techniques have been proposed to solve the problem in the literature, which can be categorized into linear and nonlinear control approaches [11]- [14]. Examples of the latter include sliding mode controls [15], fuzzy logic control [16], [17], artificial neural network [18], and deep learning [19]. Aside from that, the Gaussian process (GP) has also been employed to its capability to create flexible nonlinear nonparametric models [20]. ...
p>A two-wheeled self-balancing robot (TWSBR) is an underactuated system that is inherently nonlinear and unstable. While many control methods have been introduced to enhance the performance, there is no unique solution when it comes to hardware implementation as the robot’s stability is highly dependent on accuracy of sensors and robustness of the electronic control systems. In this study, a TWSBR that is controlled by an embedded NI myRIO-1900 board with LabVIEW-based control scheme is developed. We compare the performance between proportional-integral-derivative (PID) and linear quadratic regulator (LQR) schemes which are designed based on the TWSBR’s model that is constructed from Newtonian principles. A hybrid PID-LQR scheme is then proposed to compensate for the individual components’ limitations. Experimental results demonstrate the PID is more effective at regulating the tilt angle of the robot in the presence of external disturbances, but it necessitates a higher velocity to sustain its equilibrium. The LQR on the other hand outperforms PID in terms of maximum initial tilt angle. By combining both schemes, significant improvements can be observed, such as an increase in maximum initial tilt angle and a reduction in settling time.</p
... In [20], the authors proposed a control laboratory project that helped students gain practical experience in feedback control concepts. The project used a portable self-balancing robot to guide students through the essential stages of control system design. ...
Kinematics is a fundamental topic in engineering, robotics, mechatronics, and control systems and significantly resolves some of these fields’ most pressing issues. It is essential to assess the balance between a topic’s theoretical framework and its empirical validation to succeed in engineering. Educational tools have gained significant attention for their ability to enhance the learning experience by providing the hands-on experiences necessary to assess theoretical frameworks and empirical validations. This paper presents a system incorporating state-of-the-art features, including a fuzzy controller enabling precise control of a linear actuator and a USB camera, to provide an interactive experience. The USB camera captures the position of the actuator, providing real-time visual feedback and allowing the students to validate their theoretical understanding through practical experiments. Precision, accuracy, resolution, and the implementation of the fuzzy controller are measured to evaluate the whole system’s performance. The design, implementation, and control of our educational electrical linear actuator for teaching kinematics concepts contribute to a practical educational tool and advance interactive learning approaches in the field.
... No additional material was found. [20] This article presents a laboratory project of a self-balancing robot. Students are guided to execute the essential stages of control system design in the MATLAB/Simulink environment, up to the implementation and validation of the closed loop. ...
This article presents the methodology for developing a control laboratory project that provides practical experience based on the ABET criteria. The project is structured around a portable and cheap ball and beam whose integrated system is made using printed circuit boards as the first task. For the expression of the plant, students are guided to execute the essential stages of the control system design, from system modeling, through the design of the basic or advanced control strategy in the MATLAB and Arduino environment, to the implementation and validation of the closed loop. The proposed methods are clear and direct, greatly fostering the understanding of feedback control techniques and enabling students to gain extensive knowledge in practical implementations of control systems. The methodology is easy to interpret and modify in order to adopt it to any computer, allowing for the implementation of new practical tasks in control courses. Additionally, application examples and student-focused comments are included. This paper describes, in detail, the implementation and development of six laboratory practices for control courses, which have been developed based on ESP32 and other existing equipment.
... Dentro de su formación se puede encontrar con el control de motores mediante el control difuso, como lo muestran en [7]. También se pueden ejecutar asignaciones dedicadas en el campo de la robótica, aportando calidad, portabilidad y reducción de recursos [8]. Mientras que en [9] se puede observar un accionamiento en corriente continua usando un sistema difuso multi-cascada. ...
Los procesos de enseñanza – aprendizaje requieren una constante actualización y la incorporación de nuevos enfoques. Para esto las instituciones de educación superior necesitan realizar importantes inversiones económicas o buscar alternativas de menor costo. Por ello en este artículo se presenta la implementación de un algoritmo de control difuso en una tarjeta embebida Arduino Uno. El diseño del controlador difuso se realiza con cinco funciones de membresía tanto a la entrada como a la salida SISO (entrada simple/salida simple). Como entrada se tiene el valor del error acumulado que es la diferencia entre el valor deseado y el valor medido. Las pruebas de simulación se efectuaron en el entorno de diagrama de bloques Simulink de MATLAB. Mientras que las pruebas experimentales se desarrollaron en una estación didáctica que imita un proceso de control de presión industrial. También se obtienen otros parámetros que son parte de las curvas de proceso para un mejor análisis. De esta manera se valida esta propuesta, ofreciendo información para futuras investigaciones
... In [23], a testing methodology was developed for creating control systems. It helped to discover and implement a mathematical model, estimate different motor model parameters, get familiar with the hardware and software to develop the controller, and use the AT-Mega328 microprocessor Unit (MCU) as the Central Processing Unit (CPU) device capable of handling the fuzzy logic controller. ...
Brushed (B) and Brushless (BL) DC motors constitute the cornerstone of mechatronic systems regardless their sizes (including miniaturized), in which both position and speed control tasks require the application of sophisticated algorithms. This manuscript addresses the initial step using time series analysis to forecast Back EMF values, thereby enabling the elaboration of real-time adaptive fine-tuning strategies for PID controllers in such a control system design problem. An Auto-Regressive Moving Average (ARMA) model is developed to estimate the DC motor parameter, which evolves in time due to the system’s imperfection (i.e., unpredictable duty cycle) and influences the closed-loop performance. The methodology is executed offline; thus, it highlights the applicability of collected BDC motor measurements in time series analysis. The proposed method updates the PID controller gains based on the Simulink ™ controller tuning toolbox. The contribution of this approach is shown in a comparative study that indicates an opportunity to use time series analysis to forecast DC motor parameters, to re-tune PID controller gains, and to obtain similar performance under the same perturbation conditions. The research demonstrates the practical applicability of the proposed method for fine-tuning/re-tuning controllers in real-time. The results show the inclusion of the time series analysis to recalculate controller gains as an alternative for adaptive control.
... As a nonlinear control method, fuzzy control does not need to provide the actual model of the observation object but transforms human knowledge or experience into certain control rules, which are expressed in computer language and realize the control of the target by imitating human thinking. Fuzzy control is mainly based on knowledge expression and fuzzy reasoning and uses certain fuzzy logic rules to implement specific decisions [18,19]. Common fuzzy control systems generally include data input and output modules, fuzzy control center, execution unit and measurement mechanism. ...
The existing routing protocols for wireless sensor networks were not reasonable in design, which limited their application. Most of the existing studies did not take into account the energy consumption of the network and the balanced use of the energy of sensor nodes, which led to the unsatisfactory application effect of wireless sensor networks in some fields. Therefore, from the perspective of energy balance in wireless sensor networks, this paper proposed a construction method of an energy balance routing protocol in wireless sensor networks based on a fuzzy control strategy. Firstly, based on the analysis of the basic composition of wireless sensor networks and the structure of sensor nodes, this paper expounded the basic process of wireless data transmission and summarized the classification and characteristics of routing protocols in wireless sensor networks from different angles. Secondly, according to the node data transmission characteristics of wireless sensor networks, the energy balance use model of sensor nodes was established, and the design method of the energy balance routing protocol based on fuzzy control strategy was proposed, and the data transmission link was optimized. Finally, through experimental comparative analysis, the results showed that the energy balanced routing protocol proposed in this paper can effectively realize the energy balanced use of the network data transmission process. Compared with other common routing protocols, the wireless sensor network routing protocol proposed in this paper can not only improve the data transmission efficiency and reduce the data redundancy but also save energy consumption and prolong the network running time. The design method of routing protocol proposed in this paper will be conducive to the optimization and application of routing protocol in wireless sensor networks and provide a theoretical basis for the related research of wireless sensor networks.
... However, the adoption of the online or distance learning scheme opened a new chapter in the understanding of the mental health stability of teachers and students. Online education is not limited to distance education, as it refers to a grouping of teaching-learning procedures completed in cyberspace [9][10][11]. Mental health problems can have a negative impact on the physical and psychological wellbeing of students and predispose them to many unhealthy behaviors [8]. ...
Citation: Vital-Lopez, L.; García-Garcia, R.; Rodríguez Reséndiz, J.; Paredes-García, W.J.; Zamora-Antuñano, M.A.; Oluyomi-Elufisan, T.; Rodríguez Reséndiz, H.; Álvarez Sánchez, A.R.; Cruz-Pérez, M.A. The Impacts of COVID-19 on Technological and Polytechnic University Teachers. Sustainability 2022, 14, 4593. https://
... However, the adoption of the online or distance learning scheme opened a new chapter in the understanding of the mental health stability of teachers and students. Online education is not limited to distance education, as it refers to a grouping of teaching-learning procedures completed in cyberspace [9][10][11]. Mental health problems can have a negative impact on the physical and psychological wellbeing of students and predispose them to many unhealthy behaviors [8]. ...
University teachers have adapted to different situations during the development of distance learning due to the pandemic caused by the COVID-19 virus. This study was conducted by assigning a data collection instrument to 993 teachers who are part of 15 technological universities (TUs) and 7 polytechnic universities (PUs) to determine how they were affected by COVID-19. The questions asked were related to the social, economic, academic, emotional, and health effects experienced. The results show that 63% of the teachers working online complained that online teaching invaded their family privacy; 56% pointed out that working from home and the virtual classes affected their performance as teachers; 90% of the teachers thought that they dedicated too much extra to preparing for their classes; 15% were stressed; 4% felt negative under the new teaching scheme of virtual classes; finally, 38% of the teachers stated that repeated interaction with electronic devices had a lot of negative impacts on their emotional wellbeing. By means of a G-test, it was determined that gender was independent from the studied effects. Through a multiple correspondence analysis (MCA), it was determined that, of the total number of teachers who responded to the questionnaire, half were comfortable with the online teaching model and the other half were not. The most impacted effects were the economic, training and connectivity independently from the gender.
... The controller is customized for the thrust system, which requires appropriate modification of the fuzzy PID controller [26][27][28]. Many scholars have studied fuzzy control in various aspects and algorithms [29,30]. Castillo et al. [31] presented a comparative analysis of Type-1 and Type-2 fuzzy controllers to drive an omnidirectional mobile robot in line-following tasks using line detection images. ...
The tunnel boring machine (TBM) is widely used in tunnel construction projects. The thrust system plays a crucial role to drive the machine ahead and support gripper shoes stably while tunneling. More and more attention has been paid to the pressure and velocity regulation efficiency as the TBM advances in complex rock conditions to ensure the stabilization of the tunneling process. A thrust hydraulic control system, assembled with a proportional pressure reducing valve, is established with system operating parameters. The mathematical model of the thrust electro-hydraulic system is revealed. To improve the control characteristics of the thrust system, a self-tuning fuzzy PID controller is introduced in the pressure and velocity regulation procedures. After that, tests on a Φ2.5 m scaled TBM test rig are carried out. The test results show that the thrust system adopting the fuzzy PID controller results in less oscillation and a smoother regulation process. It takes less time to reach the target goal of pressure regulation with less vibration during the pressure regenerating periods, and both systems of conventional PID controller and fuzzy PID controller are qualified in velocity regulation movements. The proposed control methods show better benefits in reduction of vibrations and shorter time of regulation to stable conditions, which extends the machine’s life and affects the acceleration of the tunneling process.
... In this process, the unsupervised learning algorithm based on machine learning divides the clustering of high-resolution images into two parts. First, high-resolution images are collected from network nodes through the map stage of unsupervised learning algorithm, and the high-resolution images are divided into several small data sets with data descriptive characteristics as indicators [17]. Then, in the reduce stage of unsupervised learning algorithm, unstructured data sets are represented. ...
Aiming at the problem of low baud rate of traditional high-resolution image synchronous acquisition fuzzy control method, a high-resolution image synchronous acquisition fuzzy control method based on machine learning is designed. By detecting the fuzzy edge information of high-resolution image, the fuzzy membership function of synchronous acquisition quantity is proposed, and the gradient amplitude of synchronous acquisition quantity of high-resolution image is calculated. The unsupervised learning algorithm based on machine learning is used to cluster the fuzzy control data, so as to determine the fuzzy space of synchronous acquisition quantity of high-resolution image, and calculate the fuzzy feature similarity, the fuzzy control of synchronous acquisition quantity of high resolution image is realized. Experimental results show that the controlled wave rate in this paper solves the problem of low wave rate in 255.63 bps/h-271.33 bps/h, and significantly improves the control accuracy.
... The creation of a laboratory project to bridge the gap between theory and practice helps students identify and work with many of the features of PV systems [92]. Including the implementation of many of the algorithms. ...
The use of photovoltaic systems for clean electrical energy has increased. However, due to their low efficiency, researchers have looked for ways to increase their effectiveness and improve their efficiency. The Maximum Power Point Tracking (MPPT) inverters allow us to maximize the extraction of as much energy as possible from PV panels, and they require algorithms to extract the Maximum Power Point (MPP). Several intelligent algorithms show acceptable performance; however, few consider using Artificial Neural Networks (ANN). These have the advantage of giving a fast and accurate tracking of the MPP. The controller effectiveness depends on the algorithm used in the hidden layer and how well the neural network has been trained. Articles over the last six years were studied. A review of different papers, reports, and other documents using ANN for MPPT control is presented. The algorithms are based on ANN or in a hybrid combination with FL or a metaheuristic algorithm. ANN MPPT algorithms deliver an average performance of 98% in uniform conditions, exhibit a faster convergence speed, and have fewer oscillations around the MPP, according to this research.
... The estimation of parameters is a widely studied problem; there are multiple works such as [1][2][3][4][5][6] in which the estimation of the parameters of the Photovoltaic Models is developed as the main object of study. It is due to the high interest in having a function that describes the dynamic behavior of the systems since its performance can be estimated as in [7], where the authors propose a sensor-less prediction system. ...
In the present work, a neuronal dynamic response prediction system is shown to estimate the response of multiple systems remotely without sensors. For this, a set of Neural Networks and the response to the step of a stable system is used. Six basic characteristics of the dynamic response were extracted and used to calculate a Transfer Function equivalent to the dynamic model. A database with 1,500,000 data points was created to train the network system with the basic characteristics of the dynamic response and the Transfer Function that causes it. The contribution of this work lies in the use of Neural Network systems to estimate the behavior of any stable system, which has multiple advantages compared to typical linear regression techniques since, although the training process is offline, the estimation can perform in real time. The results show an average 2% MSE error for the set of networks. In addition, the system was tested with physical systems to observe the performance with practical examples, achieving a precise estimation of the output with an error of less than 1% for simulated systems and high performance in real signals with the typical noise associated due to the acquisition system.
... While support teams generally exist to help faculty members learn and implement online learning, they typically support only a small group of teachers interested in teaching online. In the current situation, with so little preparation time, these teams were not able to offer to all the teachers the usual level of support given to small groups [4,[18][19][20][21]. Further, the temptation to compare online learning with classroom instruction in these circumstances is strong. ...
This descriptive study intends to identify the satisfaction perception among the teachers of the Universidad del Valle de México (UVM) concerning the use of the Microsoft Teams platform in the transition from traditional model (face-to-face) to 100% online education [Emergency Remote Teaching (ERT)]. The proposal aims to determine the perspectives of teachers regarding the use of the Microsoft Teams platform during the crisis caused by COVID-19. UVM has 6938 full-time teachers and part-time teachers who collaborated in educational programs during January-June 2020 in the 33 campuses of UVM. And an instrument was developed and applied using finite population sampling, UVM perspective of teachers, which was distributed via Google Forms. The feasibility of the data collection instrument was determined by the Cronbach’s Alpha coefficient, with a result of 0.926. The data collection period was aligned with the first isolation period: 23 March to 20 April. The results in the perception of teacher satisfaction in the different sections of the instrument established an agreement in the answers (very satisfied or satisfied) regarding values that were higher than 60% in terms of satisfaction using the equipment. The analysis of the data collected was performed to verify the proposed hypothesis with the R version 4.0 software. A G-test was performed with the Logverosimilitude coefficient to test whether the categorical variables were independent (qualitative variables that are not defined continuously). The Krammer coefficient of association was then calculated to measure the correlation.
... The work [29] reports Arduino-based projects for improving automatic control learning. More recently, works such as [30,31] report learning tools that demonstrate fuzzy techniques in a control laboratory project setting. ...
In this paper, we present the development of a low-cost multi-agent system experimental platform for teaching, and research purposes. The platform consists of train-like autonomous agents equipped with local speed estimation, distance sensing to their nearest predecessor, and wireless communications with other agents and a central coordinator. The individual agents can be used for simple PID experiments in a classroom or laboratory setting, while a collection of agents are capable of performing decentralized platooning with cooperative adaptive cruise control in a variety of settings, the latter being the main goal of the platform. The agents are built from low cost components and programmed with open source software, enabling teaching experiences and experimental work with a larger number of agents that would otherwise be possible with other existing solutions. Additionally, we illustrate with experimental results some of the teaching activities that the platform is capable of performing.
... Traditionally, various solvers in MATLAB such as ordinary differential equations (ODE) are used for teaching and applying these design concepts. However, majority of Robot Analysis course students have struggled to understand these complex design concepts because of their different background knowledge [4][5][6][7][8], limited hands-on experience on using MATLAB, students can have different learning preferences, and the requirement of advance competence level in MATLAB especially for Robot Analysis projects. ...
The present article reports a computer-aided teaching strategy, which is novel, using a MATLAB toolbox (i.e. SimMechanics) for project-based learning in a mechanical engineering robotics course (i.e. robot analysis). The effectiveness of the proposed teaching strategy was evaluated using multiple lenses of critical reflection such as student-reflection using numerous students’ surveys, and students’ grades comparison. Furthermore, the performance of this new teaching strategy was compared with a traditional teaching method, during which, traditional MATLAB solvers (e.g. ODE) were employed rather than SimMechanics. The results showed that the proposed teaching strategy helped students more than traditional teaching method to better understand and visualize ‘robot analysis’ concepts such as 3D drawing, dynamic modelling, and solving differential equations. The majority of students were more involved in learning, were able to achieve better learning outcomes, and performances.
... Such requirements ensure that the controller algorithm successfully stabilizes the system in the close vicinity of the desired state based on the estimation results [1][2][3]. If these conditions are not satisfied, then the system can easily be driven to unwanted states, which may eventually damage the hardware [4][5][6][7]. As a result, the estimator algorithm should be both analyzed carefully during dynamic conditions and tuned properly in order to provide accurate and robust results [8][9][10][11]. ...
This paper presents an open-source environment for development, tuning, and performance evaluation of magnetic, angular rate, and gravity-based (MARG-based) filters, such as pose estimators and classification algorithms. The environment is available in both ROS/Gazebo and MATLAB/Simulink, and it contains a six-degrees of freedom (6 DOF) test bench, which simultaneously moves and rotates an MARG unit in the three-dimensional (3D) space. As the quality of MARG-based estimation becomes crucial in dynamic situations, the proposed test platform intends to simulate different accelerating and vibrating circumstances, along with realistic magnetic perturbation events. Moreover, the simultaneous acquisition of both the real pose states (ground truth) and raw sensor data is supported during these simulated system behaviors. As a result, the test environment executes the desired mixture of static and dynamic system conditions, and the provided database fosters the effective analysis of sensor fusion algorithms. The paper systematically describes the structure of the proposed test platform, from mechanical properties, over mathematical modeling and joint controller synthesis, to implementation results. Additionally, a case study is presented of the tuning of popular attitude estimation algorithms to highlight the advantages of the developed open-source environment.
... It is necessary to create a new control loop if more than one variable is required to be regulated. In addition, the processes to be controlled must present a linear behavior, which is why they are inefficient for non-linear systems [19][20][21]. ...
This research focused on developing a methodology that facilitates the learning of control engineering students, specifically developing skills to design a complete control loop using fuzzy logic. The plant for this control loop is a direct current motor, one of the most common actuators used by educational and professional engineers. The research was carried out on a platform developed by a group of students. Although the learning techniques for the design and implementation of controllers are extensive, there has been a delay in teaching techniques that are relatively new compared to conventional control techniques. Then, the hands-on laboratory offers a tool for students to acquire the necessary skills in driver tuning. In addition to the study of complete systems, the ability to work in a team is developed, a fundamental skill in the professional industrial area. A qualitative and quantitative analysis of student learning was carried out, integrating a multidisciplinary project based on modern tools.
... The performance of all the aforementioned controllers is tested by numerical simulations. On the other hand, regarding the use of inverted pendulum-type systems in education, in [19], a cheap portable arduino-based self-balancing robot is used to implement different strategies of control. All the different stages in the design and implementation process such as modeling, parameter estimation, programming, etc., are considered. ...
This work presents the realization of a complicated stabilization problem for a three inverted pendulum links-based mobile robot. The actuators of the mobile robot are direct current motors that have tachometer couplings to measure both the position and speed of the wheels and links. Using direct measurements under load and analyzing the deceleration curve, the motor parameters are determined experimentally. A mathematical model of the robot is obtained via the Euler–Lagrange equations. Next, the nonlinear model is linearized and discretized. Based on this discrete LTI model, an optimal controller is designed. The states and disturbances are estimated using a robust detector. Both the controller and detector are implemented in the robot processor. Numerical simulations and experimental tests show a good performance of the controller despite the presence of disturbances.
This article describes a research study on an electromechanical system with saturation, where a fuzzy hybrid controller with integral action and anti-windup is applied. The study focuses on implementing this Integral Fuzzy Logic Controller (IFLC) on a Field-Programmable Gate Array (FPGA) board. The fuzzy controllers, known for their effectiveness in handling disturbances and saturations, are used in a parallel structure. To optimize the performance of the controller, the Particle Swarm Optimization (PSO) technique is employed to tune the membership functions and feedback loop gains. The complex algebraic concepts and Type 1 fuzzy logic algorithms are transformed into mathematical equations suitable for VHSIC Hardware Description Language (VHDL). The proposed controller is co-simulated using Vivado and Xilinx® System Generator (XSG) tools on both software and hardware platforms. The utilization of fixed-point data propagation in the controller's structure ensures optimized implementation methods. The performance index of our controller surpasses that of a conventional Proportional-Integral-Derivative (PID) controller, demonstrating superior efficacy in regulating the system dynamics. To verify the efficacy of the proposed control strategy, a thorough comparison is done using control simulations between it and previous PID systems. The results show a 31% decrease in speed overshoot.
The principal objective of this handbook is to present state-of-the-art of educational robotics and how they can be harnessed to facilitate learning. To do this, a systematic approach has been utilized to present fi ndings and discussions of hundred infl uential journal articles in the fi eld of educational robotics in the past six years (2018-2023). The potential educational opportunities and challenges as a result of the incorporation of robotics in education are presented for educators and researchers to explore best practices in using robotics for learning and create eff ective solutions to tackle emerging problems. By analyzing educational robotics, the handbook attempts to place emphasis on how robotics can be leveraged to provide sound pedagogical principles essential for the development of transferable skills needed in our contemporary society. The handbook provides the reader with the key research organizations and journals that have extensively contributed to the field of educational robotics in the past six years. Additionally, the popular and relevant terms and theories in educational robotics are provided to help the reader gain background knowledge of the subject matter. The hundred infl uential academic articles obtained from the systematic search of literature are further categorized into seven thematic areas in educational robotics to highlight the key areas researchers are focusing on. The handbook aims to guide a reader in comprehending how diff erent types of robots are utilized to promote learning among diff erent types ofstudents in different contexts and in diff erent disciplines of study
Two-wheel self-balancing robot, as one of the most advantaged robot attitude control optimization at present, needs to be adjusted by scientific attitude correction algorithm after being disturbed, so as to ensure that the robot can still operate normally under the condition of disturbance. After understanding the basic principle of the two-wheel self-balancing robot control system, this paper analyzes the function and efficiency of the current robot automatic control system according to the design of the actual controller and the modeling and simulation of the whole system.
This study suggests a strategy for creating a low-cost two-wheeled balancing scooter with a simpler system that can work similarly to the commercial ones on the market. A simple system will help people to understand how it works and how to build it. The mechanical parts were made from simple hollow bar iron. Wheelbarrow wheels were attached to two electric bicycle motors, and the controller was using an 8-bit microcontroller running a proportional derivative (PD) controller. PD controller only is not enough to run the scooter with a passenger smoothly. Some strategies were added to overcome some non-linear problems due to the use of low-cost components. Finally, the system is successfully built and can be ride by a 65 kgs weight of rider. The scooter can turn left or right, and even to make a 360-degree spot-rotation. © 2022 Institute of Advanced Engineering and Science. All rights reserved.
An intelligent autonomous robot is in demand for robotic operations in the fields such as industry, medical, bionics, military. For any machine, designed to follow a precise sequence of instructions, self-positioning, path framing, map architecture, and obstacle prevention are the prerequisites of navigation. This paper presents a survey about the key navigation approaches explored by various authors in the last decade. The survey has a brief insight into the various approaches used for robot navigation concerning to the variable and invariable nature of the vicinity and the obstacle. The comprehensive look-over presented in this paper provides an in-depth analysis and assessment of the discrete classical and heuristic approaches used by the researchers. The research assessment is finally concluded by aggregating the complete knowledge of the various path planning techniques by reviewing the literature.
The article considers a system for monitoring the state of hydrolytospheric processes in the region. The results of pilot filtration work (PFW) at the field under consideration are presented. Based on PFW, a methodology for determining the parameters of a link approximating the static coefficients of mutual influence of producing wells is shown. Using the obtained link, the procedure for determining the optimal number of producing wells located on a given size section is shown. Using the results of PFW, the parameters of the discrete mathematical model of the hydrolyte-sphere processes of the field were verified. The technique of designing a distributed network for controlling the flow rate of producing wells of a given field is shown. Using a verified mathematical model of the hydrolyte-sphere process, the operation of a closed control system was simulated.
The laboratories of control theory are often limited to simulations and a few or none experimental tests. As in other technical subjects, practical experiments really help to understand the theory but need much time and the experimental platforms are usually expensive. This paper describes a platform that implements a universal third‐order discrete controller based on field programmable gate array (FPGA). The controller is implemented using fixed‐point arithmetic, with 17‐bit coefficients, but students can reduce the number of bits to find the resolution problems that may arise. This low‐cost platform, based on a Xilinx Spartan FPGA, allows students to try controllers just by configuring the coefficients of the controller through a computer application and a USB port. It drastically reduces the implementation time, allowing more time for design and testing. Therefore, students can try many controllers in the same laboratory session so that they can check experimentally their behavior in real prototypes and see the differences between simulations and physical systems. This platform has been applied in a real course over two academic years. The student opinion survey shows that the survey respondents consider the platform useful for more deeply understanding the subject, with an average score of 4.47/5.00 on a Likert scale (with a margin of error of 15.56% with a 95% confidence level). Besides this, the platform records the usage statistics showing that there is a relationship between the application usage and the marks in both the theory and laboratory parts.
Nowadays industrial solutions in the field of mechatronics often integrate the actuators with sensors and control units. This integration creates complex mechatronic devices. The complexity of these devices is evident, because this integration asks for communication between sensors, actuators and their control units, and communication with external control units and sensors, as well as other actuators, and often humans. To be able to prepare the students to the professional challenges they will face after finishing their studies, the teaching process at Universities and Colleges must adapt to this shift in the concept of what the industry is today, i.e. tomorrow. This research deals with the problem of developing a telepresence system at Subotica Tech as part of the project-oriented teaching process, which introduces the main aspects of modern industry, which are known as Industry 4.0. The problem is discussed by presenting a case study.
This paper presents a quaternion-based modified Madgwick filter for real-time estimation of
rigid body orientations using attitude and heading reference system (AHRS). The filter consists of a cluster
of a tri-axis accelerometer, a tri-axis magnetometer, and a tri-axis angular rate sensor. The proposed filter
implementation incorporates gyroscope bias drift compensation. Additionally, an estimated magnetic
reference along with low-pass filter are adopted to compensate for the magnetic perturbations. An
optimized Levenberg-Marquardt (LM) algorithm is applied to the Whaba’s problem to obtain the body
orientations. The hessian matrix of the algorithm was analytically derived to reduce the numerical
calculations cost. This algorithm ensures adaptive damped parameter for accurate and fast iterations. The
filter performs the calculations of rotations using quaternions rather than Euler angles, which avoids the
singularities issue associated with attitude estimation. The accelerometer and magnetometer are calibrated
off-line prior to the data fusion process. The magnetometer calibration is made using the ellipsoid fitting
technique. Experimental validation of the filter with the actual sensor data proved to be satisfactory. Testing
cases included the presence of large dynamics and magnetic perturbation were carried out. In all situations
the filter was found to converge and accurately track the rotational motions.
This paper describes the design and optimization results of a cascade fuzzy control structure developed and applied for the stabilization of an underactuated two-wheeled mobile pendulum system. The proposed fuzzy control strategy applies three fuzzy logic controllers to both provide the planar motion of the plant and reduce the inner body oscillations. Among these controllers, one is a special PI-type fuzzy logic controller designed to simultaneously ensure the linear speed and prevent high current peaks in the motor drive system. The input-output ranges and membership functions of the controllers are initially selected based on earlier studies. A complex fitness function is formulated for the quantification of the overall control performance. In this fitness function, the quality of reference tracking related to the planar motion, the efficiency of the suppression of inner body oscillations as well as the magnitude of the resulting current peaks in the driving mechanism are considered. Using the defined fitness function, the optimization of the parameters of fuzzy logic controllers is realized with the aid of particle swarm optimization, yielding the optimal possible control performance. Results demonstrate that the optimized fuzzy control strategy provides satisfying overall control quality with both fast closed loop behavior and small current peaks in the driving mechanism of the plant. The flexibility of the proposed fuzzy control strategy allows to protect the plant’s electro-mechanical parts against jerks and vibrations along with smaller energy consumption. At the end of the paper, a look-up table based implementation technique of fuzzy logic controllers is described, which requires small computational time and is suitable for small embedded processors.
This paper investigates the performance of an optimized fuzzy control structure developed for the stabilization of a naturally unstable mechatronic system. The mechatronic system is a so-called mobile wheeled pendulum consisting of two actuated coaxial wheels and an inner body which oscillates (as a pendulum) around the wheel axis during planar motion. This motion is controlled in closed loop ensuring both the stabilization of the inner body as well as the planar motion of the wheels. The control structure comprises three fuzzy logic controllers whose input-output ranges and membership functions had been defined heuristically in an earlier study. This paper analyzes the achievable control performance through the formulation of a complex performance index and application of the particle swam optimization on the parameters of the control structure. The complex performance index took into account the reference tracking errors and the extent of inner body oscillation. The optimized fuzzy logic controllers showed a remarkable 29% overall performance improvement in the closed loop dynamics compared to the performance of the initial fuzzy control parameters. The simulation results proved that the optimized closed loop behavior protects more the electro-mechanical structure of the plant since the fast reference tracking performance was achieved along with effectively limited inner body oscillations.
This paper presents a robot prototype for an undergraduate laboratory program designed to fulfill the criteria laid out by ABET. The main objective of the program is for students to learn some basic concepts of embedded systems and robotics, and apply them in practice. For that purpose, various practical laboratory exercises were prepared to teach different aspects of communications, control, mechatronics, and microcontrollers. The practicals are organized such that the students can systematically solve real-world problems. The most important feature of the presented program is that, it incorporates interdisciplinary knowledge, and inculcates technical and professional skills required in pursuing a successful career. Furthermore, students and instructors can modify the software and hardware units of the robot prototype as necessary, to explore more ideas and to apply the robot in other mechatronics-related courses. A digital electronics course taught at the Automation Department at Universidad Autónoma de Querétaro, Querétaro, Mexico, is presented as a case study in which the evaluation process was based on ABET criteria and the corresponding student outcomes. A student survey elicited students' observations of, and interest in, the learning process. The positive student feedback and student academic outcomes indicate that the inclusion of prototype had a significant impact on student academic outcomes.
This paper studies the control performances of modern and soft-computing based control solutions. Namely, the stabilization of a naturally unstable mechatronic system will be elaborated using linear-quadratic-Gaussian and cascade-connected fuzzy control schemes. The mechatronic system is a special mobile robot (so called two-wheeled mobile pendulum system) that has only two contact points with the supporting surface and its center of mass is located under the wheel axis. Due to this mechanical structure, the inner body (which acts as a pendulum between the wheels) tends to oscillate during the translational motion of the robot, thus the application of feedback control is essential in order to stabilize the dynamical system. In the first part of the paper, the mechatronic system and the corresponding mathematical model are introduced, while in the second part the aforementioned control solutions are designed for the plant. The achieved control performances are analyzed both in simulation environment and on the real mechatronic system. At the end of the paper, a performance assessment of the elaborated control solutions is given based on transient response and error integral measurements.
In this paper, the linear-quadratic-Gaussian control of a mechatronic system will be studied. The mechatronic
system is a special mobile robot (called two-wheeled mobile pendulum) having two-wheels, two contact points with the supporting surface and its center of mass is located under the wheel axis. Due to the mechanical structure, the inner body (which acts as a pendulum between the wheels) tends to oscillate during the translational motion of the robot, thus the application of modern control methods is essential in order to
stabilize the dynamical system. In the first part of the paper, the mechatronic system and the corresponding mathematical model are introduced, while in the second part different controllers are designed for the plant. The achieved control performances are analyzed based on simulation and implementation results.
The two-wheeled mobile pendulum system is a special mobile robot having two-wheels, two contact
points with the supporting surface and its center of mass is located under the wheel axis. Due to the mechanical structure, the intermediate body tends to oscillate during the translation motion of the robot thus the application of modern control methods is essential in order to stabilize the dynamical system. In this paper, we introduce the mechatronics construction of the robot and derive its corresponding nonlinear mathematical model as well.
A novel neural control on basis of extreme learning machines (ELMs) is proposed to control wheeled inverted pendulum vehicle, which is a human transportation platform mounted on two coaxial wheels. A dynamic self-balancing control scheme for such vehicle is constructed which depends on the single-hidden layer feedforward network approximation capability of combing ELMs to capture vehicle dynamics. It is superior to conventional intelligent control by using extreme learning machines since the proposed neural control adjusts the output weight parameters online on basis of the Lyapunov synthesis approach. Experimental results are provided to demonstrate that the vehicle can maintain upright posture stably with the external disturbances based on the proposed control scheme.
This paper introduces a method of design and implementation of a two-wheeled inverted pendulum (TWIP) robot with friction compensation. Friction in the drive mechanism is a critical factor of robot self-balancing and affects its performance. The friction parameters are identified based on the dynamic model of the drive mechanism. The dynamics of the whole robot system are obtained by the Lagrangian function method and take the robot drive mechanism friction into account. Sliding mode controllers for self-balancing and yaw motion are designed independently, although the TWIP robot is coupled as a nonlinear system. A low cost but low accuracy gyro and accelerator in consumer electronics grade is adopted to estimate the pitch angle and pitch rate. Using the sensor data from the gyro and accelerator fused with the help of a Kalman filter, the robot body pitch angle is obtained precisely, and these are the key state variables for TWIP control. The effect on the sensor installation location is analysed and corrected with innovation, and the precision of the pose estimation is improved accordingly. Several physical experiments are conducted, and the results demonstrate that the proposed method is effective.
Embedding a fuzzy controller into a microcontroller is a complex development compared to a simple PID controller. There is a possibility to choose the implementation strategy between full calculation with low memory and full memory with low calculation solution. The Lookup table (LUT) based fuzzy implementation helps to reduce the required calculation at the expense of required memory, which could be the best solution for a low-power microcontrollers. This research presents the lookup table solution for a fuzzy controller with two input and one output, where the resolution is 8-bit. The reduced 6-bit resolution LUT’s cost is only 4Kbyte memory, and the 2D linear interpolation only needs 27 operations. The fuzzy surface errors are between 2-5% compared to the original fuzzy controller developed in Matlab with double precision. This implementation is tested for DC motor controlling, and a similar solution will be suitable for controlling 18 DC motor of the Szabad(ka) hexapod robot series.
Advanced control concepts present a teaching challenge, where even at master level students benefit from these concepts being implemented and demonstrated on real hardware, rather than simply modelling the plant, applying control strategy and tuning. This paper describes one of a series of three experiments demonstrating the implementation of different control strategies using adaptive cruise control (ACC) on robot models and real robots. The experiment described here utilises the model predictive control (MPC) strategy implemented in ACC. The algorithm is realised using the graphical programming language (LabVIEW) as the design environment and National Instruments Robotics Starter Kit robot as the target hardware, with the code being deployed on a field programmable gate array (FPGA), included in the robot's architecture.
Two robotic vehicles, ‘the leader’ and ‘the follower’ are programmed to execute ACC: the velocity of the leader robot and the distance between the robots are augmented into the robot's state-space equation, to design the controller (MPC), which was then tuned for both velocity and distance tracking modes.
The experiment offers a novel idea on how to deliver this advanced control strategy in an applied and visual manner with laboratory experimentation supporting the theoretical aspects of learning. It brings to life some often stated theoretical qualities of an MPC controller, including quick rise time, minor fluctuation and a small distance tracking error, in line with current scientific papers. Thus, it demonstrates to students a clear correlation between theoretical expectations and real-life system performance whilst challenging their ability to work with real hardware.
This paper presents a low-cost hands-on experiment for a classical undergraduate controls course for non-electrical engineering majors. The setup consists of a small dc electrical motor attached to one of the ends of a light rod. The motor drives a 2-in propeller and allows the rod to swing. Angular position is measured by a potentiometer attached to the pivot point. A custom-designed circuit board produces the controlled voltage input to the motor. The target board is powered and communicates with the PC through its USB port using a virtual RS-232 port. A simple MATLAB/Simulink module has been created to read the pendulum angle and send a command signal to the motor. The module is based on Real-time Windows Target software, which allows a sampling rate of up to 200 Hz. Students are able to design and test classical PID and phase lead-lag controllers, as well as modern controllers, including state-space controller design combined with feedback linearization. A semester-long series of assignments is described that can be carried out without the need for a specialized laboratory or teaching assistants. The project was tested in a classical control systems design class of senior-level mechanical engineering students. Student feedback and survey data on the effectiveness of the modules are also presented.
As technology is evolving rapidly, the consumers of education systems, namely students, are exposed to more visual and audio media. Advertisements, computer games, movies, and all types of digital media are doing their best to attract young people's attention using the latest technologies. The question of whether or not this situation is beneficial for students is not discussed here. However, it is of vital importance to recognize the challenge that this situation poses for teachers. It is a tough job to attract the attention of students, especially at the undergraduate level, to a technical subject and motivate learning within a limited time. The control courses should also be logical, practical, up to date, and insightful. These objectives are best achieved with the aid of in-class experiments, laboratory practice, and newly emerging advances in technology.
This paper presents a novel implementation of an integral sliding-mode controller (ISMC) on a two-wheeled mobile robot (2 WMR). The 2 WMR consists of two wheels in parallel and an inverse pendulum, which is inherently unstable. It is the first time that the sliding-mode control method is employed for real-time control of a 2 WMR platform and several critical issues are addressed. First, the 2 WMR is underactuated, which uses only one actuator to achieve position control of the wheels while balancing the pendulum around the upright position. ISMC is suitable for control of the underactuated 2 WMR, because ISMC has an extra degree of freedom in control when sliding mode is achieved. In this paper, we utilize this extra degree of freedom to implement a linear nominal controller, which is found adequate in stabilizing the sliding manifold in a range around the equilibrium. Second, the 2 WMR system is in presence of both matched and unmatched uncertainties. The implemented ISMC, with an integral sliding surface and a switching term, is able to completely nullify the influence from the matched uncertainties. The implemented linear nominal controller stabilizes the sliding manifold that is subject to unmatched uncertainties. Third, references design are addressed when implementing ISMC on the 2 WMR. The effectiveness of ISMC is verified through intensive simulation and experiment results.
This paper presents low-cost experiments for a control systems laboratory module that is worth one and a third credits. The experiments are organized around the microcontroller-based control of a permanent magnet dc motor. The experimental setups were built in-house. Except for the operating system, the software used is primarily freeware or free for academic use. The objective of this module is that students-fresh from a first course in control systems theory, which introduces them to proportional-integral-derivative control and to design using Bode plots and root locus-learn how a simple modern control system is built. Student feedback and a 90-min end-of-semester practical exam show that, although the students find the experiments challenging, this module helps meet this objective. After having taken the first course and this laboratory module, the students feel that they can build control systems in addition to discussing them theoretically. This module is easy to set up and administer using the supporting material provided by the authors.
In the past decade, there has been much more research in two-wheeled robots which actively stabilize themselves. Various models and controllers have been applied both to explain and control the dynamics of two-wheeled robots. We explore the methods which have been investigated and the controllers which have been used, first for balancing and movement of two-wheeled robots on flat terrain, then for two-wheeled robots in other situations, where terrain may not be flat, where there may be secondary objectives and where the robots may have additional actuators.
The present paper discusses on development and implementation of back-propagation neural network integrated modified DAYANI method for path control of a two-wheeled self-balancing robot in an obstacle cluttered environment. A five-layered back-propagation neural network has been instigated to find out the intensity of various weight factors considering seven navigational parameters as obtained from the modified DAYANI method. The intensity of weight factors is found out using the neural technique with input parameters such as number of visible intersecting obstacles along the goal direction, minimum visible front obstacle distances as obtained from the sensors, minimum left side obstacle distance within the visible left side range of the robot, average of left side obstacle distances, minimum right side obstacle distance within the visible right side range of the robot, average of right side obstacle distances and goal distance from the robot’s probable next position. Comparison between simulation and experimental exercises is carried out for verifying the robustness of the proposed controller. Also, the authenticity of the proposed controller is verified through a comparative analysis between the results obtained by other existing techniques with the current technique in an exactly similar test scenario and an enhancement of the results is witnessed.
This paper investigates the optimized control performances of fuzzy and proportional-integral-derivative (PID) control schemes developed for the stabilization of an under-actuated mobile robot. The fuzzy control strategy had been designed in an earlier paper, its equivalent PID controller-based scheme is established first. Then a complex cost function is defined that evaluates the reference tracking performance, the efficiency of system oscillations suppression and the average current consumption in the motor drive system. The particle swarm optimization (PSO) is applied to tune both control schemes under the same circumstances by minimizing the formulated cost function. Results demonstrate that the optimized fuzzy control strategy provides the same reference tracking quality with significantly better suppression of system oscillations and current peaks compared to the optimized PID control.
This paper proposes two novel approaches to estimate accurately mobile robot attitudes based on the fusion of low-cost accelerometers and gyroscopes. The first part of the paper demonstrates the use of a special test bench that both enables simulations of various dynamic behaviors of wheeled robots and measures their real attitude angles along with the raw sensor data. These measurements are applied in a simulation environment and we outline an offline optimization of Kalman filter parameters. The second part of the paper introduces a novel adaptive Kalman filter structure that modifies the noise covariance values according to the system dynamics. The instantaneous dynamics are characterized regarding the magnitudes of both the instantaneous vibration and the external acceleration. The proposed adaptive solution measures these magnitudes and utilizes fuzzy-logic to modify the filter parameters in real time. The results show that the adaptive filter improves the overall filter convergence by a remarkable 10.9% over using the optimized Kalman filter, thereby demonstrating its efficacy as an accurate and robust attitude filter. The proposed filter performances are also benchmarked against other common methods indicating that the flexibility of the developed adaptive filter allowed it to compete and even outperform the benchmark filters.
This paper presents mobile platforms that were recently designed in support of an introductory control course. Through dedicated assignments, the students are guided to implement and validate all parts of the course on a setup, ranging from basic time-domain system identification, over root locus analysis and loop shaping PID design, to state feedback, state estimation and Kalman filtering. The platforms are flexible, allowing for numerous extensions and variations; cheap, allowing for a large pool of setups from which the students can borrow platforms to take home; and of sufficient quality, allowing the students to get maximal insight in the course material. The setups are easy to set up and administer using the supporting material provided by the authors.
Systems dynamics and automatic control is classified as one of the toughest courses in the college of engineering at Qassim University according to the statistical analysis of the final grades. This motivated us to think about a new approach to teach this course by extending the design term project to include experimental part beside the theoretical analysis. This approach has become feasible due to the publicity of the low-cost microcontrollers such as the Arduino in the recent years. In this paper, we present our experience in conducting Arduino-based projects and how we used them to support the teaching of all the automatic control subjects in the course such as the mathematical modelling, the stability analysis, the controller design and the implementation of the PID controller. It was found that the new approach improves the attention and the overall performance of the students in the course which was reflected in the students’ marks in the quizzes and exams. Moreover, it motivated the students to be creative by utilising the control theory to design new systems that can be useful for their local community.
Course objectives, like research objectives and product requirements, help provide clarity and direction for faculty and students. Unfortunately, course and laboratory objectives are not always clearly stated. Without a clear set of objectives, it can be hard to design a learning experience and determine whether students are achieving the intended outcomes of the course or laboratory. In this paper, a common set of laboratory objectives, concepts, and components of a laboratory apparatus for undergraduate control systems laboratories were identified. A panel of 40 control systems faculty members completed a multi-round Delphi survey to bring them toward consensus on the common aspects of their laboratories. These panelists identified 15 laboratory objectives, 26 concepts, and 15 components common to their laboratories. Then an 45 additional faculty members and practitioners completed a follow-up survey to gather feedback on the results. In both surveys, each participant rated the importance of each item. While average ratings differed slightly between the two groups, the order in which the items were ranked was similar. Important examples of common learning objectives include connecting theory to what is implemented in the laboratory, designing controllers, and modeling systems. The most common component in both groups was MathWorks software. Some of the common concepts include block diagrams, stability, and PID control. Defining common aspects of undergraduate control systems laboratories enables common development, detailed comparisons, and simplified adaptation of equipment and experiments between campuses and programs.
The extension of the traditional hands-on laboratories to the Internet, in which labs are remotely accessible to the users to perform experiments, is still a challenge for education in engineering. In this paper, we present a remote refrigeration laboratory that allows students, trainees, and engineers to get acquainted with control aspects of mechanical refrigeration systems. Thanks to a university-industry partnership, the remote lab is hosted in an industrial site and it can be accessed by means of a client-server communication and an ad-hoc designed LabVIEW-based user interface, that allows to monitor and control the plant. The user can conduct both open- and closed-loop experiments on a typical vapor compression cycle refrigeration system, testing different control architectures that range from standard regulators to data-driven PID controllers.
In this paper the efficiency of using VNS (Variable Neighborhood Search) algorithm for forming four member heterogeneous groups within CSCL (Computer supporting collaborative learning) is analyzed. A mathematical model, based on Kagan's instructions, was created and then the VNS algorithm, the metaheuristic for solving the mathematical optimization problems, was applied to the model. The proposed VNS method is tested on a set of problem instances and results are compared with the optimal results obtained by CPLEX solver applied to the proposed formulation. VNS method showed better performance in terms of execution time and being able to solve large problem instances.
The CSCL was applied to three groups of the first year college students, each consisting of 172 students. These three groups were divided into smaller ones of four students: by using VNS algorithm in 2015 (group E), by using Kagan's instructions in 2014 (group K), and randomly in 2013 (group R).
The students were tested before and after CSCL of calculus contents. The statistical analysis shows that the students divided by VNS algorithm had significantly better results than the students divided randomly. But the students divided by VNS algorithm were as successful as the students divided without computer. This means that the students’ learning achievement in calculus contents is better when they are divided by VNS than randomly, but is as successful as the cooperative learning in heterogeneous groups when VNS was not applied.
The Industrial Electronics Laboratory at the Swiss Federal Institute of Technology (EPFL) in Lausanne has built a prototype of a revolutionary two-wheeled vehicle. Due to its configuration with two coaxial wheels, each of which is coupled to a DC Motor, the vehicle is able to do stationary U-turns. A control system, made up of two decoupled state space controllers, pilots the motors so as to keep the system in equilibrium. See http://leiwww.epfl.ch/joe for a video demonstration of JOE.
Nowadays, engineers rely on simulation environments to get fast, accurate results to develop complex engineering systems. This paper presents a simulation platform that is useful for students to investigate quadcopter systems. Based on real-time simulation results, the performance of the quadcopter under self-tuning fuzzy PID controllers was compared and further investigated. © 2016 Wiley Periodicals, Inc. Comput Appl Eng Educ; View this article online at wileyonlinelibrary.com/journal/cae; DOI 10.1002/cae.21769
In this paper, the fuzzy control of a mechatronic system will be studied. The mechatronic system is a special mobile robot (called two-wheeled mobile pendulum) that has two contact points with the supporting surface and its center of mass is located under the wheel axis. Due to the mechanical structure, the inner body (which acts as a pendulum between the wheels) tends to oscillate during the translational motion of the robot, thus the application of complex control solutions is essential in order to stabilize the dynamical system. In the first part of the paper the mechatronic system and the corresponding mathematical model are introduced, while in the second part the design and implementation of different fuzzy controllers are elaborated for the plant. The achieved control performances are analyzed based on simulation and implementation results.
Robotics is becoming a mainstream phenomenon, entering all areas of our lives. In addition to cutting-edge research and development, robotics is becoming equally important in the classroom and home education. Numerous educational kits have appeared on the market recently, ranging from simple toolboxes and toys to complex, configurable R&D sets. Their value in formal teaching lies in modularity and the applicability of the associated curriculum. Some kits have already attracted major crowds of users, forming strong communities. The aim of this article is to review the currently available educational robotics kits along with their possible usability in formal education, focusing the analysis on system capabilities, modularity, and teaching materials available. The summary of these teaching aids should ease the decisions of robotics experts and instructors when choosing their tools for teaching and demonstration.
Keeping up with novel methods and keeping abreast of new applications are crucial issues in engineering education. In brain research, one of the most significant research areas in recent decades, many developments have application in both modern engineering technology and education. New measurement methods in the observation of brain activity open a new frontier in engineering applications. Electroencephalogram (EEG)-based brain activity observation processes are very promising and have been used in several engineering studies, primarily for the implementation of control tasks. This paper presents the development, implementation, and assessment of an EEG-based engineering education project, in which engineering students applied the theory they had learned and improved their knowledge and skills in the area of observation and evaluation of electrical signals generated by brain activity and measured by biosensors. The main project goal was to develop and test a brain-computer interface that is able to measure the average attention level. The effectiveness of this project-based learning was evaluated by student questionnaire responses and analysis of students' exam results; students who had participated in the project were shown to have higher levels of acquired knowledge.
Advanced Control of Wheeled Inverted Pendulum Systems is an orderly presentation of recent ideas for overcoming the complications inherent in the control of wheeled inverted pendulum (WIP) systems, in the presence of uncertain dynamics, nonholonomic kinematic constraints as well as underactuated configurations. The text leads the reader in a theoretical exploration of problems in kinematics, dynamics modeling, advanced control design techniques and trajectory generation for WIPs. An important concern is how to deal with various uncertainties associated with the nominal model, WIPs being characterized by unstable balance and unmodelled dynamics and being subject to time-varying external disturbances for which accurate models are hard to come by. The book is self-contained, supplying the reader with everything from mathematical preliminaries and the basic Lagrange-Euler-based derivation of dynamics equations to various advanced motion control and force control approaches as well as trajectory generation method. Although primarily intended for researchers in robotic control, Advanced Control of Wheeled Inverted Pendulum Systems will also be useful reading for graduate students studying nonlinear systems more generally.
The free hardware platforms have become very important in engineering education in recent years. Among these platforms, Arduino highlights, characterized by its versatility, popularity and low price. This paper describes the implementation of four laboratory experiments for Automatic Control and Robotics courses at the University of Alicante, which have been developed based on Arduino and other existing equipment. Results were evaluated taking into account the views of students, concluding that the proposed experiments have been attractive to them, and they have acquired the knowledge about hardware configuration and programming that was intended.
A nonlinear H∞ controller is designed and applied for two-wheeled self-balanced vehicles, which are underactuated mechanical systems with input coupling. The main objective is, in the presence of exogenous disturbances, to ensure that the inclination angle of the pendulum (controlled DOF) is led to the upper vertical position, while the angular velocity of the wheels (the time-derivative of the remaining DOF) can be set in a desired reference value. Thus, the angular position of the wheels (remaining DOF) is driven to steady state, i.e., it is maintained stabilized (static equilibrium) (ϕ˙=0rad/s), or at least its velocity (mechanical equilibrium) (ϕ˙=const.rad/s). The proposed controller considers the whole dynamics of the system into its structure, ensuring that the overall system is closed-loop stable. Furthermore, an improvement of the nonlinear H∞ control tuning method for mechanical systems is developed. Experimental results are carried out with a real two-wheeled vehicle in the presence of external disturbances, unmodeled dynamics and from extreme initial conditions.
It is frequently claimed that the students must have an active role in building and transforming their own knowledge, and the teacher’s labor is to provide the students the necessary tools in order to reach specific learning objectives, included in a course program. This paper presents an aerial robotic system as a toolkit, and proposes a series of activities focused on the learning in automation and robotics. These proposed activities have been designed based upon the project-based learning methodology, and they facilitate the achievement of the learning objectives presented by Spanish automation committee(CEA) in conjunction with The International Society of Automation (ISA) to satisfy the Accreditation Board for Engineering and Technology (ABET) standard. The toolkit and the activities are oriented to impulse the practical teaching, giving the student additional motivation and, in consequence, improving his or her active role. Besides, the toolkit and the activities give the teacher a tool in which it is possible to assess the students learning process.
LEGO© Mindstorms is a widely spread affordable education robotic platform, that has recently gained native support from the Mathworks© simulation environment Simulink. The pros and cons of the integrated Mindstorms/Simulink framework are actually illustrated through a complex model based control design project featuring a self-stabilized bicycle, that represents a proper example of the rapid prototyping capability of the platform. The importance of such an integration is discussed taking into account the history and the results of the LEGO-based learning activities held at the Control Systems Laboratory of the University of Florence for graduate and undergraduate courses. © 2015 Wiley Periodicals, Inc. Comput. Appl. Eng. Educ. 9999:1–12, 2015; View this article online at wileyonlinelibrary.com/journal/cae; DOI 10.1002/cae.21666
In this article, we introduce our recent development of small-sized experimental devices for control research and education, with a special focus on the use of open-source technologies such as Arduino and Processing. Arduino is a pronominal open-source hardware whose architecture, implementation and other necessary resources are accessible to every users, while Processing is its software counterpart which supports rapid development of controller/interface programs without much expertise. We demonstrate their advantage with a kinematic nonholonomic system called the trident snake robot and an under-actuated mechanical system called the inverted unicycle robot.
In this paper, a sliding mode controller (SMC) is proposed for control of a wheeled inverted pendulum (WIP) system, which consists of a pendulum and two wheels in parallel. The control objective is to use only one actuator to perform setpoint control of the wheels while balance the pendulum around the upright position, which is an unstable equilibrium. When designing the SMC for the WIP system, various uncertainties are taken into consideration, including matched uncertainties such as the joint friction, and unmatched uncertainties such as the ground friction, payload variation, or road slope. The SMC proposed is capable of handling system uncertainties and applicable to general underactuated systems with or without input coupling. For switching surface design, the selection of the switching surface coefficients is in general a sophisticated design issue because those coefficients are nonaffine in the sliding manifold. In this work, the switching surface design is transformed into a linear controller design, which is simple and systematic. By virtue of the systematic design, various linear control techniques, such as linear quadratic regulator (LQR) or linear matrix inequality (LMI), can be incorporated in the switching surface design to achieve optimality or robustness for the sliding manifold. To further improve the WIP responses, the design of reference signals is addressed. The reference position for the pendulum is adjusted according to the actual equilibrium of the pendulum, which depends on the size of the friction and slope angle of the traveling surface. A smooth reference trajectory for the setpoint of the wheel is applied to avoid abrupt jumps in the system responses, meanwhile the reaching time of the switching surface can be reduced. The effectiveness of the SMC is validated using intensive simulations and experiment testings.
This paper presents a novel implementation of a Takagi-Sugeno-type fuzzy logic controller (FLC) on a two-wheeled mobile robot (2WMR), which consists of two wheels in parallel and an inverse pendulum. The control objective of the 2WMR is to achieve position control of the wheels while keeping the pendulum around the upright position that is an unstable equilibrium. The novelties of this work lie in three aspects. First, the FLC is a synthesized design which utilizes both heuristic knowledge and model information of the 2WMR system. The FLC structure, including the fuzzy labels, membership functions, and inference, is chosen based on heuristic knowledge about the 2WMR. The output parameters of the FLC are determined by comparing the output of the FLC with that of a linear controller at certain operating points, which avoids the difficulty and tediousness in manual tuning. The linear controller is designed based on a linearized model of the 2WMR system. Second, the proposed FLC is a simple and realizable design for real implementation. Only two fuzzy labels are adopted for each fuzzy variable. Sixteen fuzzy rules are used with eight output parameters and four range parameters for the membership functions to be determined. Third, the proposed FLC is successfully implemented on a real-time 2WMR for regulation and setpoint control tasks. Satisfactory responses are achieved when the 2WMR travels not only on a flat surface but also on an inclined surface. Through comprehensive experiment-based investigations, the effectiveness of the proposed FLC is validated, and the FLC shows superior performance than the existing methods.
To improve the computational efficiency and dynamic performance of low cost Inertial Measurement Unit (IMU)/magnetometer integrated Attitude and Heading Reference Systems (AHRS), this paper has proposed an effective Adaptive Kalman Filter (AKF) with linear models; the filter gain is adaptively tuned according to the dynamic scale sensed by accelerometers. This proposed approach does not need to model the system angular motions, avoids the non-linear problem which is inherent in the existing methods, and considers the impact of the dynamic acceleration on the filter. The experimental results with real data have demonstrated that the proposed algorithm can maintain an accurate estimation of orientation, even under various dynamic operating conditions.
A contest-oriented project for undergraduate students to learn implementation skills and theories related to intelligent mobile robots is presented in this paper. The project, related to Micromouse, Robotrace (Robotrace is the title of Taiwanese and Japanese robot races), and line-maze contests was developed by the embedded control system research group of the Department of Electronic Engineering, Lunghwa University of Science and Technology, Taiwan. It targets both those students who have to earn credits for a one-year special topics course and those who are just interested in making robots, and it is designed to motivate them to learn digital motion control, path planning, attitude correction, curvature detection and maze-solving algorithms. The students begin by getting acquainted with the development environment of microcontrollers, the characteristics of different sensors, and servomotor control techniques. Having learned these basic skills, they acquire further specific advanced skills and proceed to design their own mobile robots to compete in contests. The special topics course students' robots must pass examination by five teachers. Blogs and a wiki Web site for recording students' progress and experiences enhance the project's learning outcomes. Although not every student wins a prize in the contests, student feedback still shows that the contest-oriented project did motivate them to acquire the skills necessary to build and operate intelligent mobile robots.
This article presents balancing and navigation control of the balancing robot called MIPS. MIPS is a mobile inverted pendulum system whose structure is a combination of a wheeled mobile robot and an inverted pendulum system. MIPS can navigate on the horizontal plane while balancing the pendulum body. Control performance relies upon the accuracy of sensors to measure a tilted angle. Low cost gyro and tilt sensors are used and fused to detect a balancing angle. Digital filters are selectively designed for sensors to measure an inclined angle accurately with respect to different frequencies. Performances of balancing and navigation of the MIPS are tested by experimental studies through remote control.
The emerging, powerful fuzzy control paradigm has led to the worldwide success of countless commercial products and real-world applications. Fuzzy control is exceptionally practical and cost-effective due to its unique ability to accomplish tasks without knowing the mathematical model of the system, even if it is nonlinear, time varying and complex. Nevertheless, compared with the conventional control technology, most fuzzy control applications are developed in an ad hoc manner with little analytical understanding and without rigorous system analysis and design. Fuzzy Control and Modeling is the only book that establishes the analytical foundations for fuzzy control and modeling in relation to the conventional linear and nonlinear theories of control and systems. The coverage is up-to-date, comprehensive, in-depth and rigorous. Numeric examples and applications illustrate the utility of the theoretical development. Important topics discussed include: • Structures of fuzzy controllers/models with respect to conventional fuzzy controllers/models • Analysis of fuzzy control and modeling in relation to their classical counterparts • Stability analysis of fuzzy systems and design of fuzzy control systems • Sufficient and necessary conditions on fuzzy systems as universal approximators • Real-time fuzzy control systems for treatment of life-critical problems in biomedicine Fuzzy Control and Modeling is a self-contained, invaluable resource for professionals and students in diverse technical fields who aspire to analytically study fuzzy control and modeling. © 2000 by the Institute of Electrical and Electronics Engineers, Inc.
As the use of robotic mechanisms in various fields increases, the dynamics of many kinds of mechanism have to be thoroughly understood and analysed for safe and stable operation. This study is concerned with the enhancement of floor-driving ability for a two-wheeled inverted-pendulum-type autonomous vehicle. This type of robotic mechanism is innately unstable, therefore stabilization of the robot's body posture is primarily needed. For more stable driving at high speeds, the exact dynamics of this robotic mechanism was investigated using Kane's dynamic modelling. By analysing the dynamics and the system as a whole, the vehicle's stability at higher speeds was improved. The experimental results with various types of motion confirmed the enhancement of the robot's driving ability.
This paper deals with remote access to a real laboratory equipment using contemporary computer and network technology for creating the environment that will enable a remote user to perform the required laboratory exercises and control the laboratory equipment. Architecture and characteristics of WebLab will be described with special attention to the latest implemented laboratory experiment for control of the coupled water tanks (using LabVIEW). This paper will also give results of researches among student population in order to determine advantages and effects of using web laboratory in control engineering education. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 19: 538–549, 2011
An attractive and instructive approach for teaching basis of fuzzy logic-based controller design steps and effects of properties of the controller to control system by using MATLAB environment is presented in this paper. All design stages are developed in MATLAB's graphical user interface (GUI). Source codes used for both controller and to define systems to be controlled are written in separated script files using MATLAB language. Maximum and minimum values of the parameters that belong to membership functions (MFs) and rule base table are determined by using step responses and error graphics of the systems. Two different examples are given to demonstrate the usefulness of the developed tool and to visualize effect of changes of fuzzy logic-based controller parameters. © 2005 Wiley Periodicals, Inc. Comput Appl Eng Educ 13: 10–25, 2005; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20026
The aim of the paper is to demonstrate a design of a low-cost mobile robotics experiment using LEGO Mindstorms Robotic Invention System kit, Handy Board microcontroller board, CMU camera, and SRF04 sonar sensor. The experiment is designed to be used as a laboratory session of a course on Fundamentals of Autonomous Robots. This hands-on course aims to foster students' interests from different fields to autonomous mobile robotics and improve the education in this area. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 20: 203–213, 2012
Neural and fuzzy courses are widely offered at graduate and undergraduate level due to the successful applications of neural and fuzzy control to nonlinear and unmodeled dynamic systems, including electrical drives. However, teaching students a neuro-fuzzy controlled electrical drive in a laboratory environment is often difficult for schools with limited access to expensive equipment facilities. Therefore, computer simulations and dedicated software are needed to assist the students in visualizing the concepts and to provide graphical feedback during the learning process. In this article, an educational software is proposed for the neuro-fuzzy control of induction machine drives. The tool helps students learn the application of neuro-fuzzy control of electrical drives. The software has a flexible structure and graphical user interface. The neuro-fuzzy architecture, the motor and load parameters can be easily changed in the developed software. Neuro-fuzzy control performance of induction motors can be monitored graphically for various control structures and current controllers Comput Appl Eng Educ 14: 211–221, 2006; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20082