Consensus tracking problem for linear fractional multi-agent systems with initial state error

In this paper, we discuss the consensus tracking problem by introducing two iterative learning control (ILC) protocols (namely, Dα-type and PDα-type) with initial state error for fractional-order homogenous and heterogenous multi-agent systems (MASs), respectively. The initial state of each agent is fixed at the same position away from the desired one for iterations. For both homogenous and heterogenous MASs, the Dα-type ILC rule is first designed and analyzed, and the asymptotical convergence property is carefully derived. Then, an additional P-type component is added to formulate a PDα-type ILC rule, which also guarantees the asymptotical consensus performance. Moreover, it turns out that the PDα-type ILC rule can further adjust the final performance. Two numerical examples are provided to verify the theoretical results

Performance Improvement of Low-Cost Iterative Learning-Based Fuzzy Control Systems for Tower Crane Systems

This paper is dedicated to the memory of Prof. Ioan Dzitac, one of the fathers of this journal and its founding Editor-in-Chief till 2021. The paper addresses the performance improvement of three Single Input-Single Output (SISO) fuzzy control systems that control separately the positions of interest of tower crane systems, namely the cart position, the arm angular position and the payload position. Three separate low-cost SISO fuzzy controllers are employed in terms of first order discrete-time intelligent Proportional-Integral (PI) controllers with Takagi-Sugeno-Kang Proportional-Derivative (PD) fuzzy terms. Iterative Learning Control (ILC) system structures with PD learning functions are involved in the current iteration SISO ILC structures. Optimization problems are defined in order to tune the parameters of the learning functions. The objective functions are defined as the sums of squared control errors, and they are solved in the iteration domain using the recent metaheuristic Slime Mould Algorithm (SMA). The experimental results prove the performance improvement of the SISO control systems after ten iterations of SMA

Control Theory in Engineering

The subject matter of this book ranges from new control design methods to control theory applications in electrical and mechanical engineering and computers. The book covers certain aspects of control theory, including new methodologies, techniques, and applications. It promotes control theory in practical applications of these engineering domains and shows the way to disseminate researchers’ contributions in the field. This project presents applications that improve the properties and performance of control systems in analysis and design using a higher technical level of scientific attainment. The authors have included worked examples and case studies resulting from their research in the field. Readers will benefit from new solutions and answers to questions related to the emerging realm of control theory in engineering applications and its implementation

Multi Agent Systems

Research on multi-agent systems is enlarging our future technical capabilities as humans and as an intelligent society. During recent years many effective applications have been implemented and are part of our daily life. These applications have agent-based models and methods as an important ingredient. Markets, finance world, robotics, medical technology, social negotiation, video games, big-data science, etc. are some of the branches where the knowledge gained through multi-agent simulations is necessary and where new software engineering tools are continuously created and tested in order to reach an effective technology transfer to impact our lives. This book brings together researchers working in several fields that cover the techniques, the challenges and the applications of multi-agent systems in a wide variety of aspects related to learning algorithms for different devices such as vehicles, robots and drones, computational optimization to reach a more efficient energy distribution in power grids and the use of social networks and decision strategies applied to the smart learning and education environments in emergent countries. We hope that this book can be useful and become a guide or reference to an audience interested in the developments and applications of multi-agent systems

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

Cooperative Strategies for Management of Power Quality Problems in Voltage-Source Converter-based Microgrids

The development of cooperative control strategies for microgrids has become an area of increasing research interest in recent years, often a result of advances in other areas of control theory such as multi-agent systems and enabled by emerging wireless communications technology, machine learning techniques, and power electronics. While some possible applications of the cooperative control theory to microgrids have been described in the research literature, a comprehensive survey of this approach with respect to its limitations and wide-ranging potential applications has not yet been provided. In this regard, an important area of research into microgrids is developing intelligent cooperative operating strategies within and between microgrids which implement and allocate tasks at the local level, and do not rely on centralized command and control structures. Multi-agent techniques are one focus of this research, but have not been applied to the full range of power quality problems in microgrids. The ability for microgrid control systems to manage harmonics, unbalance, flicker, and black start capability are some examples of applications yet to be fully exploited. During islanded operation, the normal buffer against disturbances and power imbalances provided by the main grid coupling is removed, this together with the reduced inertia of the microgrid (MG), makes power quality (PQ) management a critical control function. This research will investigate new cooperative control techniques for solving power quality problems in voltage source converter (VSC)-based AC microgrids. A set of specific power quality problems have been selected for the application focus, based on a survey of relevant published literature, international standards, and electricity utility regulations. The control problems which will be addressed are voltage regulation, unbalance load sharing, and flicker mitigation. The thesis introduces novel approaches based on multi-agent consensus problems and differential games. It was decided to exclude the management of harmonics, which is a more challenging issue, and is the focus of future research. Rather than using model-based engineering design for optimization of controller parameters, the thesis describes a novel technique for controller synthesis using off-policy reinforcement learning. The thesis also addresses the topic of communication and control system co-design. In this regard, stability of secondary voltage control considering communication time-delays will be addressed, while a performance-oriented approach to rate allocation using a novel solution method is described based on convex optimization

A Comparative Study of Vehicle Platoon with Limited Output Information in Directed Topologies

This paper aims to study and compare the effect of limited-output information in various directed topology to the performance of vehicle platoon. Two distributed controllers based on limited-output information will be compared to cooperative state variable feedback control which designed based on full-state information. The comparison will be conducted for four common directed topologies in the vehicle platoon application. Simulation analysis is performed in three scenarios, namely under normal operations, when the leader moves with constant acceleration and when the platoon is subjected to constant communication delay. Performances comparison will be observed from inter-vehicular distance response in each follower and the results will be displayed with respect to the follower vehicle index in the platoon configuration. Finally, the behavior of each control scheme in various topologies will be summarized

Commande des Systèmes Multi-agent d'Ordre Fractionnaire

This thesis focuses on the distributed coordination of fractional-order multi-agent systems under fixed directed communication graph. Firstly, formation producing with absolute damping and communication delay of fractional-order multi-agent systems is studied. A control law is proposed and some sufficient conditions are derived for achieving formation producing. However, in some scenarios, it might be desirable that all agents achieve formation and move as a group, instead of rendezvous at a stationary point. Therefore, secondly, formation producing with relative damping and communication delay is considered. Thirdly, consensus tracking of fractional-order multi-agent systems with a time-varying reference state is studied. A common control law and a control law based on error predictor are proposed, and it is shown that the control laws are effective when a communication graph has directed spanning trees. Meanwhile, it is proved that the convergence of systems is faster using the control law based on error predictor than by the common one. Finally, the above control laws are extended to achieve formation-tracking problems. In fact, in many cases information can be sent from a reference state to only its neighbor agents not to all the agents. In order to solve the above problem, an effective control law is given to achieve consensus with a constant reference state. Then, an effective general control law and an effective particular one are proposed to achieve consensus with a time-varying reference state. Furthermore, the above control laws are extended to achieve the formation tracking problemsCe travail concerne la commande des systèmes multi-agent d’ordre fractionnaire utilisant une topologie de communication fixe. Premièrement, la production en formation avec atténuation absolue et retard de communication est étudiée. Pour cela, une loi de commande et des conditions suffisantes sont proposées. Toutefois, dans certains scénarios, il est souhaitable que tous les agents atteignent la formation souhaitée tout en se déplacent en groupe, au lieu d’un rendez-vous à un point fixe. Ce cas sera traité en étudiant la production en formation avec atténuation relative et retard de communication. Troisièmement, la poursuite par consensus des systèmes avec un état de référence variable dans le temps est étudiée. Une loi de commande commune et une seconde basée sur la prédiction d’erreur sont proposées, et le problème du consensus est résolu quand le graphe de communication contient un arbre dirigé. Il a été prouvé que la convergence du système est plus rapide en utilisant la loi basée sur la prédiction d’erreur plutôt que celle de commande commune. Enfin, les lois de commande ci-dessus sont étendues au cas de la poursuite en formation. En effet, dans de nombreux cas, l'information peut être envoyée à partir d'un état de référence vers les agents voisins uniquement et non pas à l’ensemble des agents. Afin de résoudre ce problème, une loi de commande est proposée afin de résoudre le problème du consensus avec un état de référence constant. Puis, deux lois de commande sont proposées afin de résoudre le problème du consensus avec un état de référence variant dans le temps. Ces lois sont étendues pour résoudre le problème de la poursuite en formatio

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available