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This book presents a systematic study of an emerging field in the development of multi-agent systems. In a wide spectrum of applications, it is now common to see that multiple agents work cooperatively to accomplish a complex task. The book assists the implementation of such applications by promoting the ability of multi-agent systems to track — using local communication only — the mean value of signals of interest, even when these change rapidly with time and when no individual agent has direct access to the average signal across the whole team; for example, when a better estimation/control performance of multi-robot systems has to be guaranteed, it is desirable for each robot to compute or track the averaged changing measurements of all the robots at any time by communicating with only local neighboring robots. The book covers three factors in successful distributed average tracking: algorithm design via nonsmooth and extended PI control; distributed average tracking for double-integrator, general-linear, Euler–Lagrange, and input-saturated dynamics; and applications in dynamic region-following formation control and distributed convex optimization. The book presents both the theory and applications in a general but self-contained manner, making it easy to follow for newcomers to the topic. The content presented fosters research advances in distributed average tracking and inspires future research directions in the field in academia and industry.
Distributed controller design is generally a challenging task, especially for multi-agent systems with complex dynamics, due to the interconnected effect of the agent dynamics, the interaction graph among agents, and the cooperative control laws. Cooperative Control of Multi-Agent Systems: A Consensus Region Approach offers a systematic framework for designing distributed controllers for multi-agent systems with general linear agent dynamics, linear agent dynamics with uncertainties, and Lipschitz nonlinear agent dynamics. Beginning with an introduction to cooperative control and graph theory, this monograph: Explores the consensus control problem for continuous-time and discrete-time linear multi-agent systems Studies the H∞ and H2 consensus problems for linear multi-agent systems subject to external disturbances Designs distributed adaptive consensus protocols for continuous-time linear multi-agent systems Considers the distributed tracking control problem for linear multi-agent systems with a leader of nonzero control input Examines the distributed containment control problem for the case with multiple leaders Covers the robust cooperative control problem for multi-agent systems with linear nominal agent dynamics subject to heterogeneous matching uncertainties Discusses the global consensus problem for Lipschitz nonlinear multi-agent systems Cooperative Control of Multi-Agent Systems: A Consensus Region Approach provides a novel approach to designing distributed cooperative protocols for multi-agent systems with complex dynamics. The proposed consensus region decouples the design of the feedback gain matrices of the cooperative protocols from the communication graph and serves as a measure for the robustness of the protocols to variations of the communication graph. By exploiting the decoupling feature, adaptive cooperative protocols are presented that can be designed and implemented in a fully distributed fashion.
This monograph presents new theories and methods for fixed-time cooperative control of multi-agent systems. Fundamental concepts of fixed-time stability and stabilization are introduced with insightful understanding. This book presents solutions for several problems of fixed-time cooperative control using systematic design methods. The book compares fixed-time cooperative control with asymptotic cooperative control, demonstrating how the former can achieve better closed-loop performance and disturbance rejection properties. It also discusses the differences from finite-time control, and shows how fixed-time cooperative control can produce the faster rate of convergence and provide an explicit estimate of the settling time independent of initial conditions. This monograph presents multiple applications of fixed-time control schemes, including to distributed optimization of multi-agent systems, making it useful to students, researchers and engineers alike.
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.
The paradigm of ‘multi-agent’ cooperative control is the challenge frontier for new control system application domains, and as a research area it has experienced a considerable increase in activity in recent years. This volume, the result of a UCLA collaborative project with Caltech, Cornell and MIT, presents cutting edge results in terms of the “dimensions” of cooperative control from leading researchers worldwide. This dimensional decomposition allows the reader to assess the multi-faceted landscape of cooperative control. Cooperative Control of Distributed Multi-Agent Systems is organized into four main themes, or dimensions, of cooperative control: distributed control and computation, adversarial interactions, uncertain evolution and complexity management. The military application of autonomous vehicles systems or multiple unmanned vehicles is primarily targeted; however much of the material is relevant to a broader range of multi-agent systems including cooperative robotics, distributed computing, sensor networks and data network congestion control. Cooperative Control of Distributed Multi-Agent Systems offers the reader an organized presentation of a variety of recent research advances, supporting software and experimental data on the resolution of the cooperative control problem. It will appeal to senior academics, researchers and graduate students as well as engineers working in the areas of cooperative systems, control and optimization.
Assuming only neighbor-neighbor interaction among vehicles, this monograph develops distributed consensus strategies that ensure that the information states of all vehicles in a network converge to a common value. Readers learn to deal with groups of autonomous vehicles in aerial, terrestrial, and submarine environments. Plus, they get the tools needed to overcome impaired communication by using constantly updated neighbor-neighbor interchange.
Numerous examples highlight this treatment of the use of linear quadratic Gaussian methods for control system design. It explores linear optimal control theory from an engineering viewpoint, with illustrations of practical applications. Key topics include loop-recovery techniques, frequency shaping, and controller reduction. Numerous examples and complete solutions. 1990 edition.
This book focuses on the fault-tolerant cooperative control (FTCC) of multiple unmanned aerial vehicles (multi-UAVs). It provides systematic and comprehensive descriptions of FTCC issues in multi-UAVs concerning faults, external disturbances, strongly unknown nonlinearities, and input saturation. Further, it addresses FTCC design from longitudinal motions to attitude motions, and outer-loop position motions of multi-UAVs. The book’s detailed control schemes can be used to enhance the flight safety of multi-UAVs. As such, the book offers readers an in-depth understanding of UAV safety in cooperative/formation flight and corresponding design methods. The FTCC methods presented here can also provide guidelines for engineers to improve the safety of aerospace engineering systems. The book offers a valuable asset for scientists and researchers, aerospace engineers, control engineers, lecturers and teachers, and graduates and undergraduates in the system and control community, especially those working in the field of UAV cooperation and multi-agent systems.