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Engineering - Control Engineering | Cooperative Control of Multi-Agent Systems - Optimal and Adaptive Design Approaches

Cooperative Control of Multi-Agent Systems

Optimal and Adaptive Design Approaches

Lewis, F.L., Zhang, H., Hengster-Movric, K., Das, A.

2014, XX, 307 p. 80 illus., 59 illus. in color.

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  • 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

Task complexity, communication constraints, flexibility and energy-saving concerns are all factors that may require a group of autonomous agents to work together in a cooperative manner. Applications involving such complications include mobile robots, wireless sensor networks, unmanned aerial vehicles (UAVs), spacecraft, and so on. In such networked multi-agent scenarios, the restrictions imposed by the communication graph topology can pose severe problems in the design of cooperative feedback control systems.  Cooperative control of multi-agent systems is a challenging topic for both control theorists and practitioners and has been the subject of significant recent research.

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.

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.

Content Level » Research

Keywords » Agent Synchronization - Consensus Control - Cooperative Control - Multi-agent Systems - Neural Adaptive Control - Unmanned Aerial Vehicles

Related subjects » Artificial Intelligence - Computational Intelligence and Complexity - Control Engineering - Mechanical Engineering - Signals & Communication

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