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# Unmanned Aerial Vehicles: Control Methods and Future Challenges

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## Abstract

With the rapid development of computer technology, automatic control technology and communication technology, research on unmanned aerial vehicles (UAVs) has attracted extensive attention from all over the world during the last decades. Particularly due to the demand of various civil applications, the conceptual design of UAV and autonomous flight control technology have been promoted and developed mutually. This paper is devoted to providing a brief review of the UAV control issues, including motion equations, various classical and advanced control approaches. The basic ideas, applicable conditions, advantages and disadvantages of these control approaches are illustrated and discussed. Some challenging topics and future research directions are raised.

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... For ground orchard sprayers, a number of studies have shown that targetspecific profiling variable sprays are used to adjust the profiling mechanism of the profiling sprayer to match the contours of the tree canopy [39][40][41][42]. However, due to space and load constraints, UAVs cannot carry heavy equipment [43]. Therefore, in order to achieve precise Drones 2023, 7, 57 3 of 24 ...
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Background: Unmanned Aerial Vehicles (UAVs) are increasingly being used commercially for crop protection in East Asia as a new type of equipment for pesticide applications, which is receiving more and more attention worldwide. A new model of pear cultivation called the ‘Double Primary Branches Along the Row Flat Type’ standard trellised pear orchards (FT orchard) is widely used in China, Japan, Korea, and other Asian countries because it saves manpower and is suitable for mechanization compared to traditional spindle and open-center cultivation. The disease and pest efficacy of the flat-type trellised canopy structure of this cultivation is a great challenge. Therefore, a UAV spraying trial was conducted in an FT orchard, and a four-factor (SV: Spray application volume rate, FS: Flight speed, FH: Flight height, FD: Flight direction) and 3-level orthogonal test were designed. Results: These data were used to analyze the effect, including spray coverage, deposit density, coefficient of variation, and penetration coefficient on the canopy, to determine the optimal operating parameters of the UAV for pest efficacy in FT orchards. The analysis of extremes of variance showed that factor FD had a significant effect on both spray coverage and deposition density. Followed by factor FS, which had a greater effect on spray coverage (p < 0.05), and factor SV, FH, which had a greater effect on deposition density (p < 0.05). The effects of different factors on spray coverage and deposit density were FD > FS > FH > SV, FD > FH > SV > FS, in that order. The SV3-FS1-FH1-FD3, which flight along the row with an application rate of 90 L/ha, a flight speed of 1.5 m/s, and a flight height of 4.5 m, was the optimal combination, which produced the highest deposit density and spray coverage. It was determined through univariate analysis of all experimental groups, using droplet density of 25/cm2 and spray coverage of 1%, and uniformity of 40% as the measurement index, that T4 and T8 performed the best and could meet the control requirements in different horizontal and vertical directions of the pear canopy. The parameters were as follows: flight along the tree rows, application rate not less than 75 L/ha, flight speed no more than 2 m/s, and flight height not higher than 5 m. Conclusion: This article provides ample data to promote innovation in the use of UAVs for crop protection programs in pergola/vertical trellis system orchards such as FT orchards. At the same time, this project provided a comprehensive analysis of canopy deposition methods and associated recommendations for UAV development and applications.
... For torque balancing, the rotors, two by two across from each other, rotate in the same direction, and each two adjacent rotors rotate in opposite directions. Comparing a hexarotor to a quadrotor demonstrates that the hexarotor provides higher thrust force, better stability, and stronger rotor failure tolerance [1][2][3]. ...
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A robust optimal attitude controller for hexarotor helicopters is proposed. Compared to the previous research studies on hexarotors, the current study takes account of the influences of non‐linear and coupling dynamics, structured and unstructured uncertainties, external time‐varying disturbances, and input time delays. A linear time‐invariant system is derived for each Euler angle by considering the actual rotational dynamic model as a nominal non‐linear system plus an equivalent perturbation, including non‐linear and coupling dynamics, uncertainties, disturbances, and time delays. Using this approach, a Linear Quadratic Regulation controller is first designed for the nominal linear system of each angle to accomplish the desired tracking performances. Then, a robust compensator based on the robust compensation method is proposed to counteract the effects of the equivalent perturbation on the system. Moreover, the robust attitude tracking property and uniform asymptotical stability of the closed‐loop hexarotor system are proved using Lyapunov stability theory. Several simulations have been performed to demonstrate the effectiveness and robustness of the proposed controller. Finally, experimental results are provided to confirm the robust performance of the proposed controller.
... Yang et al. [11] introduced an optimal control strategy of winner-take-all model for target tracking and cooperative competition of multi-UAVs. Furthermore, Zuo et al. [12] summarized the flight control methods and future challenges of UAVs. ...
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Unmanned aerial vehicles (UAVs) can be applied in many Internet of Things (IoT) systems, e.g., smart farms, as a data collection platform. However, the UAV-IoT wireless channels may be occasionally blocked by trees or high-rise buildings. An intelligent reflecting surface (IRS) can be applied to improve the wireless channel quality by smartly reflecting the signal via a large number of low-cost passive reflective elements. This article aims to minimize the energy consumption of the system by jointly optimizing the deployment and trajectory of the UAV. The problem is formulated as a mixed-integer-and-nonlinear programming (MINLP), which is challenging to address by the traditional solution, because the solution may easily fall into the local optimal. To address this issue, we propose a joint optimization framework of deployment and trajectory (JOLT), where an adaptive whale optimization algorithm (AWOA) is applied to optimize the deployment of the UAV, and an elastic ring self-organizing map (ERSOM) is introduced to optimize the trajectory of the UAV. Specifically, in AWOA, a variable-length population strategy is applied to find the optimal number of stop points, and a nonlinear parameter a and a partial mutation rule are introduced to balance the exploration and exploitation. In ERSOM, a competitive neural network is also introduced to learn the trajectory of the UAV by competitive learning, and a ring structure is presented to avoid the trajectory intersection. Extensive experiments are carried out to show the effectiveness of the proposed JOLT framework.
... However, there are issues remaining that deserve attention [17]. ...
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Thanks to their hovering and vertical take-off and landing abilities, quadrotor unmanned aerial vehicles (UAVs) are receiving a great deal of attention. With the diversified development of the functions of UAVs, the requirements for flight performance with higher stability and maneuverability are increasing. Aiming at parameter uncertainty and external disturbance, a deep deterministic policy gradient-based active disturbance rejection controller (DDPG-ADRC) is proposed. The total disturbances can be compensated dynamically by adjusting the controller bandwidth and the estimation of system parameters online. The tradeoff between anti-interference and rapidity can be better realized in this way compared with the traditional ADRC. The process of parameter tuning is demonstrated through the simulation results of tracking step instruction and sine sweep under ideal and disturbance conditions. Further analysis shows the proposed DDPG-ADRC has better performance.
... To ensure that the yaw angle does not change when hovering, we make two groups of rotors have opposite rotation directions, i.e., the rotation directions in the same group are the same and those in different group are opposite. Obviously, this kind of mechanical structure is the same as in a traditional unmanned aerial vehicle [26]. For the convenience of formula description, the main notations used in this paper are defined in Table 1. ...
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As we know, for autonomous robots working in a complex underwater region, obstacle avoidance design will play an important role in underwater tasks. In this paper, a binocular-vision-based underwater obstacle avoidance mechanism is discussed and verified with our self-made Underwater Quadrocopter Vehicle. The proposed Underwater Quadrocopter Vehicle (UQV for short), like a quadrocopter drone working underwater, is a new kind of Autonomous Underwater Vehicle (AUV), which is equipped with four propellers along the vertical direction of the robotic body to adjust its body posture and two propellers arranged at the sides of the robotic body to provide propulsive and turning force. Moreover, an underwater binocular-vision-based obstacle positioning method is studied to measure an underwater spherical obstacle’s radius and its distance from the UQV. Due to its perfect ability of full-freedom underwater actions, the proposed UQV has obvious advantages such as a zero turning radius compared with existing torpedo-shaped AUVs. Therefore, one semicircle-curve-based obstacle avoidance path is planned on the basis of an obstacle’s coordinates. Practical pool experiments show that the proposed binocular vision can locate an underwater obstacle accurately, and the designed UQV has the ability to effectively avoid multiple obstacles along the predefined trajectory.
... The accelerated growth of UAVs in the past decade, as well as their development with enormous potential, has expanded and altered the use of Unmanned Aerial Vehicles (UAVs) across several fields including wildfire management [1], search and rescue missions [2], smart agricultural applications [3], patrolling [4], delivery of products [5], monitoring and remote surveillance and several other applications that are topic of interest in research [6]. Swarms of UAVs may enhance the performance during these missions where having coordination among multiple UAVs may enable broader mission coverage, provide more efficient operating performance by extending the lifetime of the network, completing the mission in a shorter time frame, and enhance fault tolerance in comparison to a single UAV system. ...
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The deployment of a swarm of cooperative Unmanned Aerial Vehicles (UAVs) to pursue a mission is knowing an increasing success nowadays. This is mainly because deploying a group of cooperating UAVs instead of one single UAV offers numerous advantages, including the extension of the mission coverage, fault tolerance in case of losing a UAV during a mission, and improving the data gathering accuracy. Multicast routing, on the other hand, is a critical operation for UAV swarm networks, as it facilitates critical tasks including information transmission and swarm coordination. Moreover, designing efficient multicast protocols with Quality of Service (QoS) can be challenging due to various factors such as limited energy constraints and the dynamically changing topology with 3D movement which causes frequent changes in the network topology. Therefore, in this paper, we investigate the multicast routing problem in a swarm of UAVs. We first provide a detailed classification of existing efforts in swarm routing protocols in terms of transmission strategies. And second, we propose a new Energy Efficient Inter-UAV Multicast Routing Protocol for surveillance and monitoring applications called ''COCOMA''. We illustrate through extensive simulations that COCOMA achieves the desired efficient communication backbone and Quality-of-Service. We also discuss and implement an improvement of COCOMA called COCOMA? and show that both versions are efficient and effective in term of reducing the total emission energy by at least 10 dBm compared to the state-of-art work SP-GMRF. In addition, our proposal optimizes also the End-to-End Delay, the number of hops in the routing process, and the network throughput which consequently leads to increasing the packet delivery ratio by more than to 22% compared to SP-GMRF protocol.
... The above definitions indicate that the studied tracking problem is a geometric path-following problem. 27 Combining Equations (1)-(3), we can express the second order derivative of lateral error e y and heading error e as ...
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... Unmanned aerial vehicles (UAVs) have been increasingly used in industrial production and daily life [1][2][3][4][5]. For example, UAV transportation is widely applied to the logistics industry due to rapid increase of online shopping [6][7][8]. ...
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... Attitude control of rigid bodies has been an important research topic since the middle of the last century. In recent years, attitude dynamics of rigid bodies played a key role in a variety of engineering applications, such as robots, spaceships, aircraft, satellites, airships and unmanned aerial vehicles (see [8,17,19,30,34,40,41]). It is also a unique problem in dynamics because of the fact that the configuration manifold of a rigid body is not linear, which evolves on a nonlinear manifold called a special orthogonal group, SO (3). ...
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This paper considers the attitude tracking control problem for a rigid body. In order to avoid the complexity and ambiguity associated with other attitude representations (such as Euler angles or quaternions), the attitude dynamics and the proposed control system are represented globally on special orthogonal groups. An adaptive controller based on a Lie subgroup of SO(3) is developed such that the rigid body can track any given attitude command asymptotically without requiring the exact knowledge of the inertia moment. In the presence of external disturbances, the adaptive controller is enhanced with an additional robust sliding mode term by following the same idea within the framework of SO(3). Finally, simulation results are presented to demonstrate efficiency of the proposed controllers.
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This article presents a comprehensive overview on the recent advances of miniature hybrid Unmanned Aerial Vehicles (UAVs). For now, two conventional types, i.e., fixed-wing UAV and Vertical Takeoff and Landing (VTOL) UAV, dominate the miniature UAVs. Each type has its own inherent limitations on flexibility, payload, flight range, cruising speed, takeoff and landing requirements and endurance. Enhanced popularity and interest are recently gained by the newer type, named hybrid UAV, that integrates the beneficial features of both conventional ones. In this survey paper, a systematic categorization method for the hybrid UAV's platform designs is introduced, first presenting the technical features and representative examples. Next, the hybrid UAV's flight dynamics model and flight control strategies are explained addressing several representative modeling and control work. In addition, key observations, existing challenges and conclusive remarks based on the conducted review are discussed accordingly.
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This paper presents the cascaded integration of Incremental Nonlinear Dynamic Inversion (INDI) for attitude control and INDI for position control of micro air vehicles. Significant improvements over a traditional Proportional Integral Derivative (PID) controller are demonstrated in an experiment where the quadrotor flies in and out of a 10 m/s windtunnel exhaust. The control method does not rely on frequent position updates, as is demonstrated in an outside experiment using a standard GPS module. Finally, we investigate the effect of using a linearization to calculate thrust vector increments, compared to a nonlinear calculation.
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In this paper, the effects of the rotor flapping dynamics in the control design for the model-scaled autonomous helicopter are analyzed in detail. The analysis is based on a specific model-scaled helicopter equipped with a Bell–Hiller stabilizing bar. A simplified analytic model for the flapping dynamics in hovering flight mode is derived and then expanded to the vertical flight mode. Eigenvalues of the approximated linear system indicate that flapping dynamics in both flight modes is comparatively fast and asymptotically stable. Effects of the rotor dynamics with Bell–Hiller stabilizing bar are assessed with both simulation and experimental results, indicating that static approximation of the rotor dynamics in control design is acceptable.
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In the near future, large amount of unmanned aerial vehicles (UAVs) are expected to appear in the airspace. To ensure the safety of the airspace, there are many daunting technical problems to tackle, one of which is how to navigate multiple UAVs safely and efficiently in the large-scale airspace with both static and dynamic obstacles under wind disturbances. This paper solves this problem by developing a novel data-driven multi-UAV navigation framework that combines A* algorithm with a state-of-the-art deep reinforcement learning (DRL) method. The A* algorithm generates a sequence of waypoints for each UAV and the DRL ensures that the UAV can reach each waypoint in order while satisfying all dynamic constraints and safety requirements. Furthermore, our framework significantly expedites the online planning procedure by offloading most computations to offline and limiting online computing to only path fine-tuning and dynamic obstacle avoidance. The simulation studies show the good performance of the proposed framework.
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There are two main trends in the development of unmanned aerial vehicle ( UAV ) technologies: miniaturization and intellectualization, in which realizing object tracking capabilities for a nano-scale UAV is one of the most challenging problems. In this paper, we present a visual object tracking and servoing control system utilizing a tailor-made 38 g nano-scale quadrotor. A lightweight visual module is integrated to enable object tracking capabilities, and a micro positioning deck is mounted to provide accurate pose estimation. In order to be robust against object appearance variations, a novel object tracking algorithm, denoted by RMCTer, is proposed, which integrates a powerful short-term tracking module and an efficient long-term processing module. In particular, the long-term processing module can provide additional object information and modify the short-term tracking model in a timely manner. Furthermore, a position-based visual servoing control method is proposed for the quadrotor, where an adaptive tracking controller is designed by leveraging backstepping and adaptive techniques. Stable and accurate object tracking is achieved even under disturbances. Experimental results are presented to demonstrate the high accuracy and stability of the whole tracking system.
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This paper presents a multiple observers based anti-disturbance control (MOBADC) scheme against multiple disturbances for a quadrotor unmanned aerial vehicle (UAV). The quadrotor UAV dynamics can be represented by the Newton’s second law and Lagrange–Euler formalism. The proposed control scheme consists of disturbance observer (DO) based controller and extended state observer (ESO) based controller, which are utilized in the position loop to mainly eliminate the cable suspended payload disturbance with partially known information and mitigate the wind disturbance with bounded variation. What is more, in order to reject the model uncertainty and disturbance moment, another ESO based controller is designed for the attitude loop. Using the proposed control scheme, the anti-disturbance performance can be significantly enhanced. Experimental results in the presence of wind disturbance, payload oscillating disturbance, and hybrid disturbances illustrate the robustness and effectiveness of the proposed method compared to the classical PID method.
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This article introduces a fully actuated multirotor flight system utilizing the tilting-thruster-type multirotor ( $T^3$ -multirotor), a new type of multirotor platform that enables six-controllable-degree-of-freedom flight with minimal structural heterogeneity compared to conventional multirotor designs. This new multirotor platform consists of upper and lower parts (or thruster and fuselage parts), with a unique kinematic structure and dedicated servomechanism that controls the relative attitude between the two parts. With the new mechanism, the fuselage of the $T^3$ -multirotor can control the translational and rotational motions independently of each other, allowing six-degree-of-freedom motion that was not possible with conventional multirotors. A dedicated robust control algorithm is developed based on a thorough analysis of system dynamics to derive accurate six-degree-of-freedom motion of the platform. The flight control performance of the platform is validated through simulations and actual experiments. Several flight tasks are also performed to demonstrate the potential of the $T^3$ -multirotor in overcoming the limitations of conventional multirotors.
Conference Paper
Realtime model learning proves challenging for complex dynamical systems, such as drones flying in variable wind conditions. Machine learning technique such as deep neural networks have high representation power but is often too slow to update onboard. On the other hand, adaptive control relies on simple linear parameter models can update as fast as the feedback control loop. We propose an online composite adaptation method that treats outputs from a deep neural network as a set of basis functions capable of representing different wind conditions. To help with training, meta-learning techniques are used to optimize the network output useful for adaptation. We validate our approach by flying a drone in an open air wind tunnel under varying wind conditions and along challenging trajectories. We compare the result with other adaptive controller with different basis function sets and show improvement over tracking and prediction errors.
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This paper proposes a novel robust attitude estimation algorithm for a small unmanned aerial vehicle (UAV) in the absence of GPS measurements. A synthetic sideslip angle (SSA) measurement formulated for use under the zero-angle assumption is newly proposed for a UAV without angle-of-attack (AOA)/SSA sensors to enhance the state estimation performance during a GPS outage. In addition, the nongravitational acceleration is estimated using the proposed Kalman filter and is then subtracted from the raw acceleration to yield a reliable gravity estimate. Then, a fuzzy-logic-aided adaptive measurement covariance matching algorithm is devised to adaptively reduce the weight given to disturbed acceleration and magnetic field measurements in the attitude estimation, yielding the fuzzy adaptive error-state Kalman filter (FAESKF) algorithm. Experimental flight results demonstrate that the proposed FAESKF algorithm achieves a remarkable improvement in attitude estimation compared to the conventional algorithm.
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This paper focuses on the design of a novel path following control concept for fixed-wing aircraft, which systematically incorporates the nonlinearities of the flight dynamics. By introducing an acceleration based inner loop control, feedforward acceleration demands of nonlinear 3D paths can be directly taken into account. Furthermore, the nonlinear effects of airspeed, orientation, and gravity are considered separately by implementing a cascaded design and feedback linearization. As a result, robust performance of the path following control is achieved even for wind speeds in the order of the aircraft’s airspeed and path accelerations significantly higher than the gravitational acceleration. By further including direct lift control, a high-bandwidth vertical acceleration control is developed. Results of flight experiments show that the designed control concept is particularly beneficial in terms of the tracking performance for 3D paths, the incorporation of input constraints, the robustness against wind and turbulence effects, and the ease of implementation as well as the low computational complexity.
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In this paper, a tracking flight control scheme is proposed based on a disturbance observer for a quadrotor with external disturbances. To facilitate the processing of external time-varying disturbances, it is assumed to consist of some harmonic disturbances. Then, a disturbance observer is proposed to estimate the unknown disturbance. By using the output of the disturbance observer, a flight controller of the quadrotor is developed to track the given signals which are generated by the reference model. Finally, the proposed control method is applied to flight control of the quadrotor Quanser Qball 2. The experimental results are presented to demonstrate the effectiveness of the developed control strategy.
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In this paper, a three dimensional (3-D) path-following control design for an underactuated stratospheric airship is proposed based on the parameterized path description. The desired attitude, velocity and the path parameter updating law are obtained by employing the guidance-based path-following (GBPF) principle. The resultant system possesses a cascaded structure, which consists of a guidance loop, an attitude stabilization loop and a velocity tracking loop. The stability analysis shows that the path-following error and all states of the closed-loop system are ultimately uniformly bounded. Simulation results demonstrate the effectiveness of the proposed controller.
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There has been significant interest for designing flight controllers for small-scale unmanned helicopters. Such helicopters preserve all the physical attributes of their full-scale counterparts, being at the same time more agile and dexterous. This book presents a comprehensive and well justified analysis for designing flight controllers for small-scale unmanned helicopters guarantying flight stability and tracking accuracy. The design of the flight controller is a critical and integral part for developing an autonomous helicopter platform. Helicopters are underactuated, highly nonlinear systems with significant dynamic coupling that needs to be considered and accounted for during controller design and implementation. Most reliable mathematical tools for analysis of control systems relate to modern control theory. Modern control techniques are model-based since the controller architecture depends on the dynamic representation of the system to be controlled. Therefore, the flight controller design problem is tightly connected with the helicopter modeling. This book provides a step-by-step methodology for designing, evaluating and implementing efficient flight controllers for small-scale helicopters. Design issues that are analytically covered include: • An illustrative presentation of both linear and nonlinear models of ordinary differential equations representing the helicopter dynamics. A detailed presentation of the helicopter equations of motion is given for the derivation of both model types. In addition, an insightful presentation of the main rotor's mechanism, aerodynamics and dynamics is also provided. Both model types are of low complexity, physically meaningful and capable of encapsulating the dynamic behavior of a large class of small-scale helicopters. • An illustrative and rigorous derivation of mathematical control algorithms based on both the linear and nonlinear representation of the helicopter dynamics. Flight controller designs guarantee that the tracking objectives of the helicopter's inertial position (or velocity) and heading are achieved. Each controller is carefully constructed by considering the small-scale helicopter's physical flight capabilities. Concepts of advanced stability analysis are used to improve the efficiency and reduce the complexity of the flight control system. Controller designs are derived in both continuous time and discrete time covering discretization issues, which emerge from the implementation of the control algorithm using microprocessors. • Presentation of the most powerful, practical and efficient methods for extracting the helicopter model parameters based on input/output responses, collected by the measurement instruments. This topic is of particular importance for real-life implementation of the control algorithms. This book is suitable for students and researchers interested in the development and the mathematical derivation of flight controllers for small-scale helicopters. Background knowledge in modern control is required.
Book
A Mathematical Introduction to Robotic Manipulation presents a mathematical formulation of the kinematics, dynamics, and control of robot manipulators. It uses an elegant set of mathematical tools that emphasizes the geometry of robot motion and allows a large class of robotic manipulation problems to be analyzed within a unified framework. The foundation of the book is a derivation of robot kinematics using the product of the exponentials formula. The authors explore the kinematics of open-chain manipulators and multifingered robot hands, present an analysis of the dynamics and control of robot systems, discuss the specification and control of internal forces and internal motions, and address the implications of the nonholonomic nature of rolling contact are addressed, as well. The wealth of information, numerous examples, and exercises make A Mathematical Introduction to Robotic Manipulation valuable as both a reference for robotics researchers and a text for students in advanced robotics courses.
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The attitude control of quadrotor Unmanned Aerial Vehicle (UAV) is investigated. The aim of the paper is to develop a continuous multivariable attitude control law, which drives the attitude tracking errors of quadrotor UAV to zero in finite time. Firstly, a multivariable super-twisting-like algorithm (STLA) is proposed for arbitrary order integrator systems subject to matched disturbances. A discontinuous integral term is incorporated in the control law in order to compensate the disturbances. A rigorous proof of the finite time stability of the close-loop system is derived by utilizing the Lyapunov method and the homogeneous technique. Then, the implementation of the developed method in an indoor quadrotor UAV is performed. The remarkable features of the developed algorithm includes the finite time convergence, the chattering suppression and the nominal performance recovery. Finally, the efficiency of the proposed method is illustrated by numerical simulations and experimental verification.
Article
In this brief, attitude control is investigated for a quadrotor under gust wind via a dual closed-loop control framework. In the dual closed-loop framework, active disturbance rejection control and proportional-derivative control are used in the inner and outer loops, respectively. The perturbations of gust wind are considered as dynamic disturbances, which are estimated by an extended state observer in the inner loop. Both convergence and stabilization are given for the extended state observer and the closed-loop system, respectively. Experimental results are given to show the effectiveness of the proposed method for quadrotors.
Article
This paper addresses the trajectory tracking control (i.e., outer-loop control) problem for unmanned aerial vehicles (UAVs) in the presence of modeling uncertainties and external disturbances. The kinematics and dynamics of the trajectory tracking problem are always in strict feedback form. While there is no uncertainty in the kinematics, rapidly changing uncertainties present in the dynamics makes this problem an ideal candidate for L1 adaptive backstepping control. The trajectory tracking controller serves as the outer-loop in a cascaded design architecture and supplies a reference quaternion and thrust to the inner-loop controller. The inner-loop controller in turn generates a moment demand for the control allocation module. Such an inner-outer loop architecture is modular and does away with the requirement that the commanded trajectory be four times differentiable as would be required if a single monolithic backstepping control law where to be used. Both simulations and flight tests are used to demonstrate the effectiveness of the proposed controller and how the controller tracks any twice differentiable trajectory, respectively.
Article
In practice, the parameters of the flight controller of the quadrotors are commonly tunned experimentally with respect to a certain type of reference, such as the step reference and the unit-ramp reference. In this way, the performance of the flight controller might be affected by the variations of the references in real-time flights. Besides, real-time dynamic effects such as measure nosies, external disturbances and input delays, which are usually neglected in the reported works, could easily deteriorate the performances of the flight controllers. This work is thereby motivated to develop a high-performance flight control approach utilizing a modified disturbance rejection technique for the quadrotors suffering from input delays and external disturbances. This control approach is developed in a cascaded structure and the attitude angles are chosen as the pseudo control inputs of the translational flight of the quadrotors. To facilitate the development, the dynamic model of the quadrotors is firstly formulated by including the effects of input delays, and the dynamics of the pseudo control variables are identified through real-time experiments. Based on the identified model, the flight control approach is proposed with a modified active disturbance rejection technique, which consists of a time optimal tracking differentiator, an extended state observer/predictor, and a nonlinear proportional-derivative controller. The tracking differentiator is designed to generate smooth transient profiles for the references, and the extended state observer/predictor is implemented for lumped disturbance estimation and state estimation considering the input delays. With the aid of the tracking differentiator and the extended state observer/predictor, the nonlinear proportional-derivative controller can thereby establish a fast tracking control and effectively reject the estimated disturbances. To verify the feasibilities of this development, comparative tests are carried out in both simulations and experiments. The results show that in the presence of small lumped disturbances, such as the measurement zero-drift, the steady-state errors of the proposed control approach for the ramp responses are less than 2 cm, and in the tests of sinusoidal trajectory tracking, the cross-tracking errors are less than 0.04 m. When with large disturbance airflow that is equivalent to strong breeze, the steady-state error achieved by the proposed flight controller is also less than 10 cm. All of these facts demonstrate the effectiveness of this development.
Book
The sliding mode control methodology has proven effective in dealing with complex dynamical systems affected by disturbances, uncertainties and unmodeled dynamics. Robust control technology based on this methodology has been applied to many real-world problems, especially in the areas of aerospace control, electric power systems, electromechanical systems, and robotics. Sliding Mode Control and Observation represents the first textbook that starts with classical sliding mode control techniques and progresses toward newly developed higher-order sliding mode control and observation algorithms and their applications. The present volume addresses a range of sliding mode control issues, including: *Conventional sliding mode controller and observer design *Second-order sliding mode controllers and differentiators *Frequency domain analysis of conventional and second-order sliding mode controllers *Higher-order sliding mode controllers and differentiators *Higher-order sliding mode observers *Sliding mode disturbance observer based control *Numerous applications, including reusable launch vehicle and satellite formation control, blood glucose regulation, and car steering control are used as case studies Sliding Mode Control and Observation is aimed at graduate students with a basic knowledge of classical control theory and some knowledge of state-space methods and nonlinear systems, while being of interest to a wider audience of graduate students in electrical/mechanical/aerospace engineering and applied mathematics, as well as researchers in electrical, computer, chemical, civil, mechanical, aeronautical, and industrial engineering, applied mathematicians, control engineers, and physicists. Sliding Mode Control and Observation provides the necessary tools for graduate students, researchers and engineers to robustly control complex and uncertain nonlinear dynamical systems. Exercises provided at the end of each chapter make this an ideal text for an advanced course taught in control theory.
Article
Autonomous unmanned air vehicles (UAVs) are critical to current and future military, civil, and commercial operations. Despite their importance, no previous textbook has accessibly introduced UAVs to students in the engineering, computer, and science disciplines--until now. Small Unmanned Aircraftprovides a concise but comprehensive description of the key concepts and technologies underlying the dynamics, control, and guidance of fixed-wing unmanned aircraft, and enables all students with an introductory-level background in controls or robotics to enter this exciting and important area. The authors explore the essential underlying physics and sensors of UAV problems, including low-level autopilot for stability and higher-level autopilot functions of path planning. The textbook leads the student from rigid-body dynamics through aerodynamics, stability augmentation, and state estimation using onboard sensors, to maneuvering through obstacles. To facilitate understanding, the authors have replaced traditional homework assignments with a simulation project using the MATLAB/Simulink environment. Students begin by modeling rigid-body dynamics, then add aerodynamics and sensor models. They develop low-level autopilot code, extended Kalman filters for state estimation, path-following routines, and high-level path-planning algorithms. The final chapter of the book focuses on UAV guidance using machine vision. Designed for advanced undergraduate or graduate students in engineering or the sciences, this book offers a bridge to the aerodynamics and control of UAV flight.
Article
In this paper, a non linear autopilot for a missile pitch axis is designed over a wide flight envelope. The controller is obtained by a Linear Parametrically Varying (LPV) synthesis applied to the H¥/loop-shaping criterion. The resulting controller depends on the angle of attack, the Mach number and the altitude. Robust stability and performance are firstly checked by means of linear analysis and secondly verified by using non linear simulations, in the face of aerodynamic dispersions and scheduling parameters variations.
Chapter
Conventional sliding mode control, studied in Chap. 2, and second-order sliding mode control (Chap. 4) are the most obvious choices in controlling systems with bounded matched disturbances/uncertainties. Sliding mode control laws allow us achieve to insensitivity of system’s compensated dynamics to these perturbations. The ultimate price for this insensitivity is a high-frequency (that is equal to infinity in an ideal sliding mode) switching control function that after being filtered by the plant yields self-sustained oscillations of almost zero amplitude. The main advantage of higher (second-)order sliding mode control is its ability to guarantee higher accuracy of the sliding variable stabilization at zero than conventional sliding mode control.
Article
This brief proposes a disturbance rejection control strategy for attitude tracking of an aircraft with both internal uncertainties and external disturbances. The proposed control strategy consists of a robust disturbance observer (DOB) and a nonlinear feedback controller. Specifically, a robust DOB is proposed to compensate the uncertain rotational dynamics into a nominal plant, based on which a nonlinear feedback controller is implemented for desired tracking performance. We first divide the practical rotational dynamics into the nominal part, external disturbances, and equivalent internal disturbances. Then, property of equivalent internal disturbances is explored for stability analysis. A robust DOB is optimized based on theory to guarantee disturbance rejection performance and robustness against system uncertainties. A practical nonlinear feedback controller is hence applied to stabilize the compensated system based on backstepping approach. Experiments on a quadrotor testbed show that the proposed robust DOB can suppress the external disturbances and measurement noise, with the robustness against system uncertainties.
Article
This paper addresses the robust attitude control problem of miniature quadrotors. A simplified linear dynamical model is obtained for each attitude angle, whereas nonlinear dynamics, interaxis coupling, parameter perturbations, and external disturbances are considered as uncertainties. For each channel, a linear time-invariant and decoupled robust controller are proposed based on a linear reduced-order observer and a robust compensator. The observer is applied to estimate the angular velocities, and the robust compensator is introduced for reducing the effects of uncertainties. It is proven that the estimation errors of angular velocities and angular tracking errors can converge to the given neighborhood of the origin in a finite time. Experimental results on the miniature quadrotor are presented to verify the effectiveness of the proposed control approach. Copyright © 2015 John Wiley & Sons, Ltd.
Article
The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.
Conference Paper
The dynamics and technical challenges of controlling missiles capable of high-angle-of-attack Eight are discussed. The missile control effecters discussed include thrust vectoring, reaction jet thrusters, and aerodynamic tail surfaces. A control power analysis is summarized that indicates the effectiveness of these control effecters over the missile's flight envelope. The six-degree-of-freedom dynamics for high-angle-of-attach missile Eight control are presented. Autopilot design models and nonlinear simulation results demonstrating high angle-of-attack flight are also presented.
Article
The design of output constrained control system for unmanned aerial vehicles deployed in confined areas is an important issue in practice and not taken into account in many autopilot systems. In this study, the authors address a neural networks-based adaptive trajectory tracking control algorithm for multi-rotors systems in the presence of various uncertainties in their dynamics. Given any sufficient smooth and bounded reference trajectory input, the proposed algorithm achieves that (i) the system output (Euclidean position) tracking error converges to a neighbourhood of zero and furthermore (ii) the system output remains uniformly in a prescribed set. Instead of element-wise estimation, a norm estimation approach of unknown weight vectors is incorporated into the control system design to relieve the onboard computation burden. The convergence property of the closed-loop system subject to output constraint is analysed via a symmetric barrier Lyapunov function augmented with several quadratic terms. Simulation results are demonstrated on a quadrotor model to validate the effectiveness of the proposed algorithm
Article
A 3-D path-following controller is proposed in this brief for a 6-degrees-of-freedom model-scaled autonomous helicopter. The reference path and path-following errors are newly defined using implicit expressions. On the basis of geometric analysis, a new speed error is designed for singularity avoidance. The proposed control algorithm is designed using command filtered backstepping, such that complicated solutions for derivatives of virtual controls are circumvented. It is proved that, with the proposed controller, path-following errors are locally ultimately bounded. Theoretical results are demonstrated by the numerical simulation.
Article
This paper presents an alternative method of designing a guidance controller for a small unmanned aerial vehicle (UAV) so as to perform path following under wind disturbances. The wind effects acting on UAVs need to be taken into account and eventually eliminated. To solve this problem, we adopted a disturbance observer‐based control approach. The wind information is first estimated by a nonlinear disturbance observer, then it is incorporated into the nominal path following controller to formulate a composite controller that is able to compensate wind influences. The globally asymptotic stability of the composite controller is illustrated through theoretical analysis, whereas its performance is evaluated by various simulations including the one with software‐in‐the‐loop. Initial flight tests using a small fixed‐wing UAV are carried out to demonstrate its actual performance. Copyright © 2012 John Wiley & Sons, Ltd.