Iterative Learning Control For Multi Agent Systems Coordination
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| Author | : Shiping Yang |
| Publisher | : John Wiley & Sons |
| Total Pages | : 246 |
| Release | : 2017-06-12 |
| Genre | : Technology & Engineering |
| ISBN | : 1119189047 |
A timely guide using iterative learning control (ILC) as a solution for multi-agent systems (MAS) challenges, showcasing recent advances and industrially relevant applications Explores the synergy between the important topics of iterative learning control (ILC) and multi-agent systems (MAS) Concisely summarizes recent advances and significant applications in ILC methods for power grids, sensor networks and control processes Covers basic theory, rigorous mathematics as well as engineering practice
| Author | : Shiping Yang |
| Publisher | : John Wiley & Sons |
| Total Pages | : 260 |
| Release | : 2017-03-03 |
| Genre | : Technology & Engineering |
| ISBN | : 1119189063 |
A timely guide using iterative learning control (ILC) as a solution for multi-agent systems (MAS) challenges, showcasing recent advances and industrially relevant applications Explores the synergy between the important topics of iterative learning control (ILC) and multi-agent systems (MAS) Concisely summarizes recent advances and significant applications in ILC methods for power grids, sensor networks and control processes Covers basic theory, rigorous mathematics as well as engineering practice
| Author | : Ronghu Chi |
| Publisher | : Springer Nature |
| Total Pages | : 211 |
| Release | : 2022-03-21 |
| Genre | : Technology & Engineering |
| ISBN | : 9811904642 |
This book belongs to the subject of control and systems theory. The discrete-time adaptive iterative learning control (DAILC) is discussed as a cutting-edge of ILC and can address random initial states, iteration-varying targets, and other non-repetitive uncertainties in practical applications. This book begins with the design and analysis of model-based DAILC methods by referencing the tools used in the discrete-time adaptive control theory. To overcome the extreme difficulties in modeling a complex system, the data-driven DAILC methods are further discussed by building a linear parametric data mapping between two consecutive iterations. Other significant improvements and extensions of the model-based/data-driven DAILC are also studied to facilitate broader applications. The readers can learn the recent progress on DAILC with consideration of various applications. This book is intended for academic scholars, engineers and graduate students who are interested in learning control, adaptive control, nonlinear systems, and related fields.
| Author | : Wenjun Xiong |
| Publisher | : Springer Nature |
| Total Pages | : 229 |
| Release | : |
| Genre | : |
| ISBN | : 9819709261 |
| Author | : Dong Shen |
| Publisher | : CRC Press |
| Total Pages | : 641 |
| Release | : 2023-12-22 |
| Genre | : Computers |
| ISBN | : 100382112X |
Random fading communication is a type of attenuation damage of data over certain propagation media. Establishing a systematic framework for the design and analysis of learning control schemes, the book studies in depth the iterative learning control for stochastic systems with random fading communication. The authors introduce both cases where the statistics of the random fading channels are known in advance and unknown. They then extend the framework to other systems, including multi-agent systems, point-to-point tracking systems, and multi-sensor systems. More importantly, a learning control scheme is established to solve the multi-objective tracking problem with faded measurements, which can help practical applications of learning control for high-precision tracking of networked systems. The book will be of interest to researchers and engineers interested in learning control, data-driven control, and networked control systems.
| Author | : Hyo-Sung Ahn |
| Publisher | : Springer |
| Total Pages | : 368 |
| Release | : 2019-03-29 |
| Genre | : Technology & Engineering |
| ISBN | : 3030151875 |
This monograph introduces recent developments in formation control of distributed-agent systems. Eschewing the traditional concern with the dynamic characteristics of individual agents, the book proposes a treatment that studies the formation control problem in terms of interactions among agents including factors such as sensing topology, communication and actuation topologies, and computations. Keeping pace with recent technological advancements in control, communications, sensing and computation that have begun to bring the applications of distributed-systems theory out of the industrial sphere and into that of day-to-day life, this monograph provides distributed control algorithms for a group of agents that may behave together. Unlike traditional control laws that usually require measurements with respect to a global coordinate frame and communications between a centralized operation center and agents, this book provides control laws that require only relative measurements and communications between agents without interaction with a centralized operator. Since the control algorithms presented in this book do not require any global sensing and any information exchanges with a centralized operation center, they can be realized in a fully distributed way, which significantly reduces the operation and implementation costs of a group of agents. Formation Control will give both students and researchers interested in pursuing this field a good grounding on which to base their work.
| Author | : Nikos Kolobov |
| Publisher | : Springer Nature |
| Total Pages | : 71 |
| Release | : 2022-06-01 |
| Genre | : Computers |
| ISBN | : 3031015436 |
Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning. This monograph provides a concise introduction to the subject, covering the theoretical foundations as well as more recent developments in a coherent and readable manner. The text is centered on the concept of an agent as decision maker. Chapter 1 is a short introduction to the field of multiagent systems. Chapter 2 covers the basic theory of singleagent decision making under uncertainty. Chapter 3 is a brief introduction to game theory, explaining classical concepts like Nash equilibrium. Chapter 4 deals with the fundamental problem of coordinating a team of collaborative agents. Chapter 5 studies the problem of multiagent reasoning and decision making under partial observability. Chapter 6 focuses on the design of protocols that are stable against manipulations by self-interested agents. Chapter 7 provides a short introduction to the rapidly expanding field of multiagent reinforcement learning. The material can be used for teaching a half-semester course on multiagent systems covering, roughly, one chapter per lecture.
| Author | : Zhongsheng Hou |
| Publisher | : CRC Press |
| Total Pages | : 400 |
| Release | : 2013-09-24 |
| Genre | : Technology & Engineering |
| ISBN | : 1466594187 |
Model Free Adaptive Control: Theory and Applications summarizes theory and applications of model-free adaptive control (MFAC). MFAC is a novel adaptive control method for the unknown discrete-time nonlinear systems with time-varying parameters and time-varying structure, and the design and analysis of MFAC merely depend on the measured input and output data of the controlled plant, which makes it more applicable for many practical plants. This book covers new concepts, including pseudo partial derivative, pseudo gradient, pseudo Jacobian matrix, and generalized Lipschitz conditions, etc.; dynamic linearization approaches for nonlinear systems, such as compact-form dynamic linearization, partial-form dynamic linearization, and full-form dynamic linearization; a series of control system design methods, including MFAC prototype, model-free adaptive predictive control, model-free adaptive iterative learning control, and the corresponding stability analysis and typical applications in practice. In addition, some other important issues related to MFAC are also discussed. They are the MFAC for complex connected systems, the modularized controller designs between MFAC and other control methods, the robustness of MFAC, and the symmetric similarity for adaptive control system design. The book is written for researchers who are interested in control theory and control engineering, senior undergraduates and graduated students in engineering and applied sciences, as well as professional engineers in process control.
| Author | : Masaaki Nagahara |
| Publisher | : Springer |
| Total Pages | : 0 |
| Release | : 2024-05-09 |
| Genre | : Technology & Engineering |
| ISBN | : 9783031529801 |
This textbook teaches control theory for multi-agent systems. Readers will learn the basics of linear algebra and graph theory, which are then developed to describe and solve multi-agent control problems. The authors address important and fundamental problems including: • consensus control; • coverage control; • formation control; • distributed optimization; and • the viral spreading phenomenon. Students' understanding of the core theory for multi-agent control is enhanced through worked examples and programs in the popular Python language. End-of-chapter exercises are provided to help assess learning progress. Instructors who adopt the book for their courses can download a solutions manual and the figures in the book for lecture slides. Additionally, the Python programs are available for download and can be used for experiments by students in advanced undergraduate or graduate courses based on this text. The broad spectrum of applications relevant to this material includes the Internet of Things, cyber-physical systems, robot swarms, communications networks, smart grids, and truck platooning. Additionally, in the spheres of social science and public health, it applies to opinion dynamics and the spreading of viruses in social networks. Students interested in learning about such applications, or in pursuing further research in multi-agent systems from a theoretical perspective, will find much to gain from Control of Multi-agent Systems. Instructors wishing to teach the subject will also find it beneficial.
| Author | : Hyo-Sung Ahn |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 237 |
| Release | : 2007-06-28 |
| Genre | : Technology & Engineering |
| ISBN | : 1846288592 |
This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. It presents a unified analysis and design framework that enables designers to consider both robustness and monotonic convergence for typical uncertainty models, including parametric interval uncertainties, iteration-domain frequency uncertainty, and iteration-domain stochastic uncertainty. The book shows how to use robust iterative learning control in the face of model uncertainty.
