Adaptive Backstepping Consensus Control for Nonlinear Multi-Agent Systems

Nyhet

Command Filtered Backstepping

Häftad, Engelska, 2025

Av Lin Zhao, Jinpeng Yu, China) Zhao, Lin (School of Automation, Qingdao University, China) Yu, Jinpeng (School of Automation, Qingdao University

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Adaptive Backstepping Consensus Control for Nonlinear Multi-Agent Systems: Command Filtered Backstepping offers a new design solution for students, researchers, and engineers working on distributed cooperative control problems for nonlinear multi-agent systems. The book is structured around six key topics, focusing on command filtered backstepping-based distributed adaptive consensus control. By combining command filtered backstepping techniques with adaptive control, fuzzy logic systems, neural networks, and other control approaches, the book investigates and proposes control schemes for the consensus control problem of nonlinear multi-agent systems. Readers will gain a comprehensive understanding of consensus control based on adaptive command filtered backstepping technology.

Provides a framework for dealing with various nonlinearities in multi-agent cooperative control problems
Proposes the corresponding intelligent adaptive control schemes to compensate for uncertainties and disturbances
Includes applications to demonstrate the advantages of cooperative adaptive command filtered backstepping control approaches

Produktinformation

Utgivningsdatum2025-12-08
Mått152 x 229 x undefined mm
Vikt450 g
FormatHäftad
SpråkEngelska
SerieEmerging Methodologies and Applications in Modelling, Identification and Control
Antal sidor272
FörlagElsevier Science
ISBN9780443416446

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Lin Zhao received a B.Sc. degree in Mathematics and Applied Mathematics from Qingdao University, Qingdao, China, in 2008, and a M.Sc. degree in Operational Research and Cybernetics from the Ocean University of China, Qingdao, in 2011. Zhao earned a Ph.D. degree in Applied Mathematics from Beihang University, Beijing, China, in 2016. He is currently a Professor with the School of Automation, Qingdao University. His current research interests include distributed control of multiagent systems, finite-time control, and robot control systems. Dr. Zhao was the recipient of the Shandong Province Taishan Scholar Special Project Fund and the Shandong Province Fund for Outstanding Young Scholars.Jinpeng Yu received a B.Sc. degree in Automation from Qingdao University, Qingdao, China, in 2002, and an M.Sc. degree in System Engineering from Shandong University, Jinan, China, in 2006. Yu went on to obtain a Ph.D. degree in System Theory from the Institute of Complexity Science, Qingdao University, in 2011. He is currently a Professor with the School of Automation, Qingdao University. His research interests include electrical energy conversion and motor control, applied nonlinear control, and intelligent systems. Dr. Yu was the recipient of the Shandong Province Taishan Scholar Special Project Fund and Shandong Province Fund for Outstanding Young Scholars. He has been an Associate Editor of several reputable journals.

PART I: Command Filtered backstepping and graph theory1. Introduction of Command filtered backstepping and graph theoryPART II: Adaptive consensus control for strict-feedback nonlinear multi-agent systems2. Neuroadaptive command filtered backstepping containment control for nonlinear multi-agent systemsPART III: Adaptive consensus control for nonstrict-feedback nonlinear multi-agent systems4. Observer based neuroadaptive finite-time command filtered backstepping containment control for nonlinear multi-agent systemsPART IV: Adaptive consensus control for constrained nonlinear multi-agent systems5. Observer based fuzzy adaptive command filtered backstepping consensus tracking control for nonlinear multi-agent systems with input constraints Lin Zhao, Jinpeng Yu, Qingdao University6. Fuzzy adaptive finite-time command filtered backstepping consensus tracking control for nonlinear multi-agent systems with unknown control directions7. Fuzzy adaptive finite-time command filtered backstepping consensus tracking control for nonstrict-feedback nonlinear multiagent systems with full-state constraintsPART V: Adaptive consensus control for nonlinear coopetition multi-agent systems8. Fuzzy adaptive command filtered backstepping bipartite consensus control for nonlinear coopetition multi-agent system9. Neuroadaptive finite-time command filtered backstepping bipartite consensus control for nonlinear coopetition multi-agent systemsPART VI: Adaptive consensus control for stochastic nonlinear multi-agent systems10. Fuzzy adaptive finite-time command filtered backstepping consensus tracking control for stochastic nonlinear multi-agent systems11. Fuzzy adaptive fast finite-time command filtered backstepping containment control for stochastic nonlinear multi-agent systemsPART VII: Applications of command filtered backstepping based adaptive consensus control12. Adaptive command filtered backstepping asymptotic consensus tracking control for multiple manipulator systems13. Adaptive finite-time command filtered backstepping containment control for multiple manipulator systems14. Adaptive finite-time command filtered backstepping containment control for multiple spacecraft systems15. Observer based finite-time command filtered backstepping containment control for multiple spacecraft systems