Imre J. Rudas

• DSc, DhC
• Professor Emeritus at Óbuda University, Budapest

Ametamodel establishes the constructs and rules governing the creation of models within a specific modeling methodology, such as model-based systems engineering (MBSE), which has gained increasing popularity among researchers and practitioners. The absence of a universally accepted metamodel can lead to various issues, which have not been adequatel...

Grasping and object manipulation have been considered key domains of Cyber-Physical Systems (CPS) since the beginning of automation, as they are the most common interactions between systems, or a system and its environment. As the demand for automation is spreading to increasingly complex fields of industry, smart tools with sensors and internal de...

Many similarity, distance, association, and correlation measures for binary data, 2x2 tables, and sets are used in ecology, biology, and social sciences in pattern recognition, machine learning, and data analysis. The Jaccard similarity measure is widely used in these tasks. We consider several extensions of this measure using the negation of binar...

Artificial Intelligence (AI) is becoming more ubiquitous throughout our lives. As our reliance on this technology increases, ensuring human operators maintain an adequate level of trust is integral to their safe and effective operations. To facilitate the appropriate level of operator trust in AI, a mechanism to continuously evaluate and calibrate...

Negation of probability distributions (PD) was initially introduced by Yager as a transformation of probability distributions representing linguistic terms like High Price, into probability distributions representing linguistic terms like Not High Price. Further, different negations of PD and formal definitions of negations of probability distribut...

We propose a method of calculating the correlation between frequency distributions defined on a finite set of categories. The method is based on the general approach to constructing an invertible correlation function on a set with involutive operation. This correlation function is constructed using a suitable similarity (or dissimilarity) function...

Recent problems in robotics can sometimes only be tackled using machine learning technologies, particularly those that utilize deep learning (DL) with transfer learning. Transfer learning takes advantage of pretrained models, which are later fine-tuned using smaller task-specific datasets. The fine-tuned models must be robust against changes in env...

Cognitive computers (κC) are intelligent processors advanced from data and information processing to autonomous knowledge learning and intelligence generation. This study presents a retrospective and prospective review of the odyssey toward κC empowered by transdisciplinary basic research and engineering advances. A wide range of fundamental theori...

The International Journal of Artificial Intelligence and Autonomous Systems (AIAS) is a new platform for rigorous and rapid publication of latest research findings and industrial applications in the contemporary fields of AI and autonomous systems. AIAS welcomes research articles on the theoretical, computational, cognitive, and empirical aspects o...

In this article, a velocity-free adaptive controller is proposed for the tracking control of servo mechanisms with friction compensation. A continuously differentiable friction model is employed to compensate for the dominant friction nonlinearity of servo mechanisms. Besides, a projection-type adaptive law is applied to handle parameter uncertaint...

Chemotherapy optimization based on mathematical models is a promising direction of personalized medicine. Personalizing, thus optimizing treatments, may have multiple advantages, from fewer side effects to lower costs. However, personalization is a complicated process in practice. We discuss a mathematical model of tumor growth and therapy optimiza...

The paper presents the method of measuring the similarity and difference in the frequency distributions of one categorical variable for different levels of another variable. This method calculates the similarity and correlation between the rows of the contingency table. In this work, we use it for the analysis of associations of cognitive indicator...

In this study, we developed a Nonlinear Model Predictive Control algorithm for tumour growth regulation. It is unique from the perspective that the subjects of the optimization were the feedback gains in the state feedback kind closed control loop. During the controller design, we utilized the results of our previous qualitative analysis of the mod...

Advanced robotics and autonomous vehicles rely on filtering and sensor fusion techniques to a large extent. These mobile applications need to handle the computations onboard at high rates while the computing capacities are limited. Therefore, any improvement that lowers the CPU time of the filtering leads to more accurate control or longer battery...

An engineering model system (EMS) is a complex purposeful structure of representation and description type content that is developed during development and application; in other words, it represents the lifecycle of an industrial product. The essential improvements for systems operated that are autonomous, situation controlled, and include cyber ph...

A brain-inspired intelligent adaptive system (IAS) framework is developed toward fundamental breakthroughs in the cognitive bottleneck of humans and the incompetence of artificial intelligence (AI) under indeterministic conditions or with insufficient data. IASs have led to defense science and technology innovations for interaction-centered design...

Dual-drive gantry stage has been widely applied to various industrial manufacturing fields with its unique structural advantages, and the synchronous control accuracy of the platform is crucial to the performance of the whole motion system. Therefore, an adaptive robust synchronous control scheme based on an improved master-slave structure is propo...

The model-based controllers generally suffer from the lack of precise dynamic models. Making reliable analytical models can be evaded by soft modeling techniques, while the consequences of modeling imprecisions are tackled by either robust or adaptive techniques. In robotics, the prevailing adaptive techniques are based on Lyapunov’s “direct method...

Symbiotic autonomous systems (SAS) are advanced intelligent and cognitive systems that exhibit autonomous collective intelligence enabled by coherent symbiosis of human–machine interactions in hybrid societies. Basic research in the emerging field of SAS has triggered advanced general-AI technologies that either function without human intervention...

Concept of closed loop control appears in many fields of engineering sciences, where the output quantity of some physical system must be forced to follow some prescribed function over time, e.g., when a robotic arm endpoint must track a desired trajectory or path given as timed series of spatial coordinates. The classic approach for solving this ki...

The outbreak of the novel coronavirus and its disease COVID-19 presents an unprecedented challenge for humanity. Intelligent systems and robotics particularly are helping the fight against COVID-19 several ways. Potential technology-driven solutions in this accelerating pandemic include, but are not limited to, early detection and diagnosis , assis...

This article describes several opportunities and synergies between the IEEE Council on Radio-Frequency Identification (CRFID) and IEEE Systems, Man, and Cybernetics Society (SMCS) to initiate a roadmap study and working plan for a new model of support and collaboration among IEEE Societies and Councils in the future. We hope this will stimulate mor...

Symbiotic Autonomous Systems (SAS) are advanced intelligent and cognitive systems exhibiting autonomous collective intelligence enabled by coherent symbiosis of human-machine interactions in hybrid societies. Basic research in the emerging field of SAS has triggered advanced general AI technologies functioning without human intervention or hybrid s...

This paper studies the disturbance observer-based adaptive fuzzy finite-time control issue of strict-feedback nonlinear systems. Specifically, to meet practical application requirement, the finite-time prescribed performance is considered, which can guarantee the tracking error enters into the prescribed bounded set in a known time. A disturbance o...

Autonomous systems are an emerging AI technology functioning without human intervention underpinned by the latest advances in intelligence, cognition, computer, and systems sciences. This paper explores the intelligent and mathematical foundations of autonomous systems. It focuses on structural and behavioral properties that constitute the intellig...

A 50th birthday is an important milestone in the life of any individual and certainly in the development of collectives and organizations. January 2021 is such a milestone in the life of the IEEE T ransactions of S ystems , M an , and C ybernetics , which had its very first issue published in January 1971. Our 50th Anniversary Issue celebrate...

To commemorate the 50th anniversary of the IEEE Transactions on Systems, Man, and Cybernetics: Systems, this article examines and reports on its past to current topical coverage of systems science and engineering toward exploring the evolving focus of the research community. Results of a systematic bibliometric analysis are presented with associate...

One challenging aspect of therapy optimization and application of control algorithms in the field of tumor growth modeling is the limited number of measurable physiological signals—state variables—and the knowledge of model parameters. A possible solution to provide such information is the application of observer or state estimator. One of the most...

It is recognized that system trustworthiness is a hyperstructure embodied by the dimensions of the structural, behavioral, and system trustworthiness and associated uncertainty. This paper explores a theoretical framework of trust and trustworthiness of autonomous systems. It presents a formal study on the essences and mathematical models of system...

This article studies the asynchronous sampled-data filtering design problem for Itô stochastic nonlinear systems via Takagi-Sugeno fuzzy-affine models. The sample-and-hold behavior of the measurement output is described by an input delay method. Based on a novel piecewise quadratic Lyapunov-Krasovskii functional, some new results on the asynchronou...

Presents SMC society members who were elevated to the status of IEEE Fellow.

The ever-increasing complexity of robot applications induces the need for methods to approach problems with no (viable) analytical solution. Deep learning (DL) provides a set of tools to address this kind of problems. This survey presents a categorization of the major challenges in robotics that leverage DL technologies and introduces representativ...

The paper presents a Sugeno Adaptive Neuro-Fuzzy Inference System with parametric conjunction operations architecture, ANFIS-CX. The advantages of using parametric conjunction operations in fuzzy models are discussed, and learning rules for system identification with such operations are proposed. These learning strategies can include steepest desce...

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 embedde...

Robotics is one of the major megatrends unfolding these days. Clearly, robots are capable of doing much more outside the factories than ever imagined, and that has a great impact on the whole society. This chapter provides some practical updates and guidelines on a few exciting aspects of automated technologies: applied robotics in the industry, in...

Presents the President's message for this issue of the publication.

Self-driving-car development on the global scale has reached a point where prototypes have proven the validity of the technology in various environments. Nevertheless, an increasing debate surrounds the serial production of these systems, with some experts arguing that real, trusted autonomous-driving capabilities may be at least a decade away, whi...

This article studies the issue of adaptive neural network (NN) control for strict-feedback multi-input and multioutput (MIMO) nonlinear systems with full-state constraints and actuator hysteresis. Radial basis function NNs (RBFNNs) are introduced to approximate unknown nonlinear functions. The command filter is adopted to solve the issue of "explos...

Reports on news of interest to SMCC society members.

Self-driving cars have, in recent years, clearly become among the most actively discussed and researched topics. By all definitions, these systems, as a third robotic revolution, belong to the robotics field, despite the fact that people generally assign them to a specific domain of the automotive industry [1]. Replicating the complex task of human...

The prevailing methodology in designing adaptive controllers for strongly nonlinear systems is based on Lyapunov’s PhD Thesis he defended in 1892 to study the stability of motion of systems for the solution of the equations of motion of which no closed form analytical solutions exist. The adaptive robot controllers developed in the nineties of the...

We introduce new correlation measures for measuring similarity and association of rating profiles obtained from bipolar rating scales. Instead of the measurement based approach when the user’s rating is considered as a number measured in ordinal, interval or ratio scales we use model based approach when user’s rating is modeled by bipolar score fun...

Receding Horizon Controllers are one of the mostly used advanced control solutions in the industry. By utilizing their possibilities we are able to predict the possible future behavior of our system; moreover, we are able to intervene in its operation as well. In this paper we have investigated the possibilities of the design of a Receding Horizon...

Recounts the career and contributions of Lotfi A. Zadeh.

This paper presents a method for detecting the mechanical stiffness of micro-metric biological tissues by means of compliance tests performed with a MEMS-Technology based microgripper. Thanks to an actuating rotary comb drive working in cooperation with another sensing rotary comb drive, the system is able to recognize the tissue sample stiffness....

In general, i.e. when the kinematic construction of a redundant robot arm does not meet special requirements, the inverse kinematic task has only differential solutions that do not exist in the kinematically singular points and suffer from large angular velocity components in the vicinity of the singularities. Recently it has been pointed out that...

Łukasiewicz fuzzy systems are fuzzy systems based on Łukasiewicz implication and Łukasiewicz t-norm and t-conorm as fuzzy operations. They are deeply rooted in classical logic while being fuzzy systems, so they establish a connection between classical logic and fuzzy logic. Łukasiewicz fuzzy systems with Center of Gravity defuzzification have been...

Receding Horizon Controllers are one of the mostly used advanced control solutions in the industry. By utilizing their possibilities we are able to predict the possible future behavior of our system; moreover, we are able to intervene in its operation as well. In this paper we have investigated the possibilities of the design of a Receding Horizon...

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...

Automation of surgical processes (SPs) is an utterly complex, yet highly demanded feature by medical experts. Currently, surgical tools with advanced sensory and diagnostic capabilities are only available. A major criticism towards the newly developed instruments that they are not fitting into the existing medical workflow often creating more annoy...

In this paper the application of a recently introduced simple iterative solution of the Nonlinear Programming approach is investigated for the Adaptive Model Predictive Control of a strongly nonlinear dynamic paradigm, the Duffing oscillator. The main idea is to replace the numerically much more complex Reduced Gradient method in the optimization t...

Nonlinear Programming provides a practical, reduced-complexity solution for the realization of Model Predictive Controllers in which a cost function representing contradictory limitations is minimized under the constraints that express the dynamical properties of the system under control. For nonlinear system models and non-quadratic cost functions...

The usability of advanced control methods of physiological processes have been several times demonstrated. Advanced (i.e. MPC) control approaches cope with practical difficulties of limited measurability of the state variables, model-imprecisions, significant inter-patient variability of the available model's parameters and limitations in the sampl...

Engineering practice is increasingly relied upon virtual technologies. Recent virtual solutions ensure integration of all engineering activities using system level computer representation of complex multidisciplinary engineering product. The authors have provided research results in developing strategies for leading engineering virtual technology,...

As many studies show, there is a relation between the tissue’s mechanical characteristics and some specific diseases. Knowing this relationship would help early diagnosis or microsurgery. In this paper, a new method for measuring the viscoelastic properties of soft materials at the microscale is proposed. This approach is based on the adoption of a...

Robot-assisted Minimally Invasive Surgical techniques are becoming standard-of-care in the surgical practice. With the rapid advancement of surgical robotics, many believe that the next step is subtask automation, since it has the potential to safely improve one element of a surgery, which might be most suitable for design and execution supported b...

The min–max robust control synthesis for uncertain nonlinear systems is solved using Takagi–Sugeno fuzzy model and fuzzy state observer. Existence conditions are derived for the output feedback min–max control in the sense of Lyapunov asymptotic stability and formulated in terms of linear matrix inequalities. The convex optimization algorithm is us...

Streamlined integration of computer technologies into the surgical domain promises to open new opportunities in developing surgical techniques. Surgical Process Models (SPMs) and surgical ontologies currently under development are believed to make objective assessment and planning possible in the surgical practice. By automating subtask level ontol...

This paper is about extended application of virtual engineering principles, methodologies, and systems as a possible answer to urgent need for integrated industrial, research, and higher educational programs and processes. One of the motivations is the changed world of engineering which requires quick utilization of new findings as new context. At...

The task to distinguish between soft tissues by testing their mechanical properties is often referred to as the primary cognitive role of haptic devices. It is a common view that today's surgical simulators that are using haptic interfaces should rely on simple mechanical models of soft tissues, instead of complex, parameterized finite element mode...

Industry 4.0 can be said to be the current trend of automation and data exchange in manufacturing technologies. Originally, the term “Industrie 4.0” is from a project in the high-tech strategy of the German government, which hope to promote the computerization of manufacturing. Usually involves terms like cyber-physical systems, Internet of things,...

Breast cancer is becoming a leading cause of death among women in the world. However, it is confirmed that early detection and accurate diagnosis of this disease can ensure a long survival of the patients. This study proposes a self-validation cerebellar model articulation controller (SVCMAC) neural network which can yield high accuracy of predicat...

The traditional ways of solving various tasks “optimally” in control technology and robotics normally are based on the minimization of some cost function (or functional). On the basis of function minimization various “generalized inverse matrices” can be introduced that have special significance in the inverse kinematic tasks of redundant manipulat...