This text offers a wide selection of techniques aimed at achieving three goals: the suppression, the synchronization, and the generation of chaos. It includes introductory material reviewing the history of chaos control and key mathematical preliminaries.

Controlling Chaos achieves three goals: the suppression, synchronisation and generation of chaos, each of which is the focus of a separate part of the book. The text deals with the well-known Lorenz, Rössler and Hénon attractors and the Chua circuit and with less celebrated novel systems. Modelling of chaos is accomplished using difference equations and ordinary and time-delayed differential equations. The methods directed at controlling chaos benefit from the influence of advanced nonlinear control theory: inverse optimal control is used for stabilization; exact linearization for synchronization; and impulsive control for chaotification. Notably, a fusion of chaos and fuzzy systems theories is employed. Time-delayed systems are also studied. The results presented are general for a broad class of chaotic systems.

This monograph is self-contained with introductory material providing a review of the history of chaos control and the necessary mathematical preliminaries for working with dynamical systems.

Unifies chaos theory with fuzzy systems theory for more effective control of chaotic systems Presents the latest results on chaotification of linear systems Presents novel advanced control methods for applications to chaotic and nonlinear systems Includes supplementary material: sn.pub/extras

Autorentext

Hongjing Liang received his B.S. degree in mathematics from Bohai University, Jinzhou, China, in 2009, his M.S. degree in fundamental mathematics from Northeastern University, Shenyang, China, in 2011, and a Ph.D. degree in control theory and control engineering from Northeastern University, Shenyang, China, in 2016. He is currently working at Bohai University. His research interests include multi-agent systems, complex systems, and output regulation. Huaguang Zhang received his B.S. and M.S. degrees in control engineering from Northeastern Electric Power University, Jilin, China, 1982 and 1985, respectively, and a Ph.D. degree in thermal power engineering and automation from Southeast University, Nanjing, China, in 1991. Dr. Zhang joined the Department of Automatic Control, Northeastern University, Shenyang, China, in 1992, as a Postdoctoral Fellow. Since 1994, he has been a professor and the head of the Electric Automation Institute, Northeastern University. He has authored three English monographs and holds 30 patents. His main research interests are neural network-based control, fuzzy control, chaos control, nonlinear control, signal processing, adaptive dynamic programming (ADP) and their industrial applications. Dr. Zhang was a recipient of the Nationwide Excellent Post-Doctor, the Outstanding Youth Science Foundation Award from the National Natural Science Foundation Committee of China in 2003, the Cheung Kong Scholar Award from the Education Ministry of China in 2005, and the IEEE Transactions on Neural Networks Outstanding Paper Award in 2012. He was an Associate Editor of Automatica, IEEE Transactions on Cybernetics and Neurocomputing. He is the Deputy Director of the Intelligent System Engineering Committee of Chinese Association of Artificial Intelligence.

Klappentext

Controlling Chaos offers its reader an extensive selection of techniques to achieve three goals: the suppression, synchronization and generation of chaos, each of which is the focus of a separate part of the book. The text deals with the well-known Lorenz, Rössler and Hénon attractors and the Chua circuit, and with less celebrated novel systems. Modeling of chaos is accomplished using difference equations and ordinary and time-delayed differential equations. The methods directed at controlling chaos benefit from the influence of advanced nonlinear control theory: inverse optimal control is used for stabilization; exact linearization for synchronization; and impulsive control for chaotification. Notably, a fusion of chaos and fuzzy systems theories is employed, with the TakagiSugeno model and the authors' own fuzzy hyperbolic model utilized in the modeling and control of chaotic systems. Time-delayed systems are also studied with many synchronization methods being explored. All the results presented are general for a broad class of chaotic systems.

This monograph is self-contained with introductory material providing a review of the history of chaos control and the necessary mathematical preliminaries for working with dynamical systems.

Controlling Chaos will be of interest to academics from electrical, systems, mechanical and chemical engineering backgrounds working in control theory related to nonlinear dynamical and chaotic systems and to graduate students of chaos control.

The Communications and Control Engineering series reports major technological advances which have potential for great impact in the fields of communication and control. It reflects research in industrial and academic institutions around the world so that the readership can exploit new possibilities as they become available.

Inhalt
Overview.- Preliminaries of Nonlinear Dynamics and Chaos.- Entrainment and Migration Control of Chaotic Systems.- Feedback Control of Chaotic Systems.- Synchronizing Chaotic Systems Based on Feedback Control.- Synchronizing Chaotic Systems via Impulsive Control.- Synchronization of Chaotic Systems with Time Delay.- Synchronizing Chaotic Systems Based on Fuzzy Models.- Chaotification of Nonchaotic Systems.