Cooperative Control of Nonlinear Networked Systems
Description
Cooperative Control of Nonlinear Networked Systems is concerned with the distributed cooperative control of multiple networked nonlinear systems in the presence of unknown non-parametric uncertainties and non-vanishing disturbances under certain communication conditions. It covers stability analysis tools and distributed control methods for analyzing and synthesizing nonlinear networked systems. The book presents various solutions to cooperative control problems of multiple networked nonlinear systems on graphs.
The book includes various examples with segments of MATLAB® codes for readers to verify, validate, and replicate the results. The authors present a series of new control results for nonlinear networked systems subject to both non-parametric and non-vanishing uncertainties, including the cooperative uniformly ultimately bounded (CUUB) result, finite-time stability result, and finite-time cooperative uniformly ultimately bounded (FT-CUUB) result. With some mathematical tools, such as algebraic graph theory and certain aspects of matrix analysis theory introduced by the authors, the readers can obtain a deeper understanding of the roles of matrix operators as mathematical machinery for cooperative control design for multi-agent systems.
Cooperative Control of Nonlinear Networked Systems is a valuable source of information for researchers and engineers in cooperative adaptive control, as its technical contents are presented with examples in full analytical and numerical detail, and graphically illustrated for easy-to-understand results. Scientists in research institutes and academics in universities working on nonlinear systems, adaptive control and distributed control will find the book of interest, as it contains multi-disciplinary problems and covers different areas of research.
Reviews / Votes
"It is not only a reference textbook for the researchers, but also can be used as an excellent graduate textbook." (Peijun Wang, zbMATH 1422.93003, 2019)More details
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Persons
Prof. Yongduan Song received the Ph.D. degree in electrical and computer engineering from Tennessee Technological University, USA, in 1992. He held a tenured Full Professor position with North Carolina A&T State University in USA from 2004 to 2008 and a Langley Distinguished Professor position with the National Institute of Aerospace, VA, USA, from 2005 to 2008. He was one of the six Langley Distinguished Professors with the National Institute of Aerospace, Founding Director of Cooperative Systems at NIA. He is currently the Dean of the School of Automation, Chongqing University, and the Founding Director of the Institute of Smart Systems at Chongqing University. He has been serving as an Associate Editor for several prestigious scientific journals, including IEEE Trans. on Automatic Control , IEEE Trans. on Neural Networks and Learning Systems , IEEE Trans. on Intelligent Transportation Systems , IET Control Theory and Applications etc. Prof. Song has received several competitive research awards from the National Science Foundation, the National Aeronautics and Space Administration, the U.S. Air Force Office of Scientific Research, the U.S. Army Research Office, and the U.S. Naval Research Office. His research interests include intelligent systems, guidance navigation and control, bio-inspired adaptive and cooperative systems, rail traffic control and safety, and smart grid.
Dr. Yujuan Wang received the Ph.D. degree in control theory and control engineering from Chongqing University, China, in 2016. From 2014 to 2015, she has been a visiting scholar with the Department of Electrical Engineering at University of Texas at Arlington. She was a Research Associate with the Department of Electrical and Electronic Engineering in The University of Hong Kong from 2017 to 2018. She is currently a Research Fellow with School of Automation in Chongqing University. Dr. Wang has been serving as an active reviewerfor several prestigious scientific journals, including IEEE Trans. on Automatic Control , Automatica , IEEE Trans. on Neural Networks and Learning Systems etc. Her research interests include nonlinear systems, multi-agent systems, distributed control, cooperative adaptive control, and fault-tolerant control.Content
Chapter 1. Introduction.- Chapter 2. Preliminaries.- Chapter 3. Lyapunov Analysis for Cooperative Adaptive Consensus under Undirected Graph.- Chapter 4. Cooperative Adaptive Consensus Control for Uncertain Multi-agent Systems with nth-Order Dynamics under Undirected Graph.- Chapter 5. Cooperative Adaptive Consensus for Multi-Agent Systems under Directed Topology.- Chapter 6. Finite-time Leaderless Consensus Control for Systems with First-Order Uncertain Dynamics.- Chapter 7. Finite-time Consensus for Systems with Second-Order Uncertain Dynamics under Undirected Topology.- Chapter 8. Finite-time Consensus for Systems with Second-Order Uncertain Dynamics under Directed Topology.- Chapter 9. Finite-time Leaderless Consensus Control for Systems with high-Order Uncertain Dynamics.
