Offering readers a wealth of cutting-edge, Riccati-based design techniques for various forms of control, this self-contained text stress-tests the reliability of the methods outlined with rigorous stability analyses and detailed control design algorithms.
Cooperative Control of Multi-Agent Systems extends optimal control and adaptive control design methods to multi-agent systems on communication graphs. It develops Riccati design techniques for general linear dynamics for cooperative state feedback design, cooperative observer design, and cooperative dynamic output feedback design. Both continuous-time and discrete-time dynamical multi-agent systems are treated. Optimal cooperative control is introduced and neural adaptive design techniques for multi-agent nonlinear systems with unknown dynamics, which are rarely treated in literature are developed. Results spanning systems with first-, second- and on up to general high-order nonlinear dynamics are presented.
Each control methodology proposed is developed by rigorous proofs. All algorithms are justified by simulation examples. The text is self-contained and will serve as an excellent comprehensive source of information for researchers and graduate students working with multi-agent systems.
Introduction to Synchronization in Nature and Physics and Cooperative Control for Multi-agent Systems on Graphs.- Algebraic Graph Theory and Cooperative Control Consensus.- Part I D istributed Optimal Design for Cooperative Control in Multi-agent Systems on Graphs.- Local Optimal Design for Cooperative Control in Multi-agent Systems on Graphs.- Riccati Design for Synchronization of Discrete-Time Systems.- Cooperative Globally Optimal Control for Multi-agent Systems on Directed Graph Topologies.- Graphical Games: Distributed Multi-player Games on Graphs.- Part II Distributed Adaptive Control for Multi-agent Cooperative Systems.- Graph Laplacian Potential and Lyapunov Functions for Multi-agent Systems.- Cooperative Adaptive Control for Systems with First-Order Nonlinear Dynamics.- Cooperative Adaptive Control for Systems with Second-Order Nonlinear Dynamics.- Cooperative Adaptive Control for Higher-Order Nonlinear Systems.
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Inhaltsverzeichnis
Introduction to Synchronization in Nature and Physics and Cooperative Control for Multi-agent Systems on Graphs.- Algebraic Graph Theory and Cooperative Control Consensus.- Part I Distributed Optimal Design for Cooperative Control in Multi-agent Systems on Graphs.- Local Optimal Design for Cooperative Control in Multi-agent Systems on Graphs.- Riccati Design for Synchronization of Discrete-Time Systems.- Cooperative Globally Optimal Control for Multi-agent Systems on Directed Graph Topologies.- Graphical Games: Distributed Multi-player Games on Graphs.- Part II Distributed Adaptive Control for Multi-agent Cooperative Systems.- Graph Laplacian Potential and Lyapunov Functions for Multi-agent Systems.- Cooperative Adaptive Control for Systems with First-Order Nonlinear Dynamics.- Cooperative Adaptive Control for Systems with Second-Order Nonlinear Dynamics.- Cooperative Adaptive Control for Higher-Order Nonlinear Systems.
Klappentext
Cooperative Control of Multi-Agent Systems extends optimal control and adaptive control design methods to multi-agent systems on communication graphs. It develops Riccati design techniques for general linear dynamics for cooperative state feedback design, cooperative observer design, and cooperative dynamic output feedback design. Both continuous-time and discrete-time dynamical multi-agent systems are treated. Optimal cooperative control is introduced and neural adaptive design techniques for multi-agent nonlinear systems with unknown dynamics, which are rarely treated in literature are developed. Results spanning systems with first-, second- and on up to general high-order nonlinear dynamics are presented.
Each control methodology proposed is developed by rigorous proofs. All algorithms are justified by simulation examples. The text is self-contained and will serve as an excellent comprehensive source of information for researchers and graduate students working with multi-agent systems.
Gives the reader convenient Riccati-based design techniques for a various forms of control with single- to high-order dynamics
Demonstrates the reliability of the methods described with rigorous stability analysis and detailed control design algorithms
Self-contained providing the reader with solid background and comprehensive cutting-edge research in the same source
