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Analysis and Control of Complex Dynamical Systems [electronic resource] : Robust Bifurcation, Dynamic Attractors, and Network Complexity / edited by Kazuyuki Aihara, Jun-ichi Imura, Tetsushi Ueta.

Contributor(s): Aihara, Kazuyuki [editor.] | Imura, Jun-ichi [editor.] | Ueta, Tetsushi [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Mathematics for Industry: 7Publisher: Tokyo : Springer Japan : Imprint: Springer, 2015Description: XIV, 211 p. 103 illus., 45 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9784431550136.Subject(s): Engineering | System theory | Physics | Complexity, Computational | Vibration | Dynamical systems | Dynamics | Engineering | Vibration, Dynamical Systems, Control | Complexity | Complex Networks | Complex SystemsAdditional physical formats: Printed edition:: No titleDDC classification: 620 Online resources: Click here to access online
Contents:
Part I Robust Bifurcation and Control -- Dynamic Robust Bifurcation Analysis -- Robust Bifurcation Analysis Based on Degree of Stability -- Use of a Matrix Inequality Technique for Avoiding Undesirable Bifurcation -- A Method for Constructing a Robust System Against Unexpected Parameter Variation -- Parametric Control to Avoid Bifurcation Based on Maximum Local Lyapunov Exponent -- Threshold Control for Stabilization of Unstable Periodic Orbits in Chaotic Hybrid Systems -- Part II Dynamic Attractor and Control -- Chaotic Behavior of Orthogonally Projective Triangle Folding Map -- Stabilization Control of Quasi-Periodic Orbits -- Feedback Control Method Based on Predicted Future States for Controlling Chaos -- Ultra-Discretization of Nonlinear Control System with Spatial Symmetry -- Feedback Control of Spatial Patterns in Reaction-Diffusion System -- Control of Unstabilizable Switched Systems -- Part III Complex Networks and Modeling for Control -- Clustered Model Reduction of Large-Scale Bidirectional Networks -- Network Structure Identification from a Small Number of Inputs/Outputs.
In: Springer eBooksSummary: This book is the first to report on theoretical breakthroughs on control of complex dynamical systems developed by collaborative researchers in the two fields of dynamical systems theory and control theory. As well, its basic point of view is of three kinds of complexity: bifurcation phenomena subject to model uncertainty, complex behavior including periodic/quasi-periodic orbits as well as chaotic orbits, and network complexity emerging from dynamical interactions between subsystems. Analysis and Control of Complex Dynamical Systems offers a valuable resource for mathematicians, physicists, and biophysicists, as well as for researchers in nonlinear science and control engineering, allowing them to develop a better fundamental understanding of the analysis and control synthesis of such complex systems.
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Part I Robust Bifurcation and Control -- Dynamic Robust Bifurcation Analysis -- Robust Bifurcation Analysis Based on Degree of Stability -- Use of a Matrix Inequality Technique for Avoiding Undesirable Bifurcation -- A Method for Constructing a Robust System Against Unexpected Parameter Variation -- Parametric Control to Avoid Bifurcation Based on Maximum Local Lyapunov Exponent -- Threshold Control for Stabilization of Unstable Periodic Orbits in Chaotic Hybrid Systems -- Part II Dynamic Attractor and Control -- Chaotic Behavior of Orthogonally Projective Triangle Folding Map -- Stabilization Control of Quasi-Periodic Orbits -- Feedback Control Method Based on Predicted Future States for Controlling Chaos -- Ultra-Discretization of Nonlinear Control System with Spatial Symmetry -- Feedback Control of Spatial Patterns in Reaction-Diffusion System -- Control of Unstabilizable Switched Systems -- Part III Complex Networks and Modeling for Control -- Clustered Model Reduction of Large-Scale Bidirectional Networks -- Network Structure Identification from a Small Number of Inputs/Outputs.

This book is the first to report on theoretical breakthroughs on control of complex dynamical systems developed by collaborative researchers in the two fields of dynamical systems theory and control theory. As well, its basic point of view is of three kinds of complexity: bifurcation phenomena subject to model uncertainty, complex behavior including periodic/quasi-periodic orbits as well as chaotic orbits, and network complexity emerging from dynamical interactions between subsystems. Analysis and Control of Complex Dynamical Systems offers a valuable resource for mathematicians, physicists, and biophysicists, as well as for researchers in nonlinear science and control engineering, allowing them to develop a better fundamental understanding of the analysis and control synthesis of such complex systems.

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