Resilient Cooperative Control and Optimization of Multi-Agent Systems

Addresses various resilient cooperative control and optimization problems of multi-agent systems that are vulnerable to physical failure and cyber attacks and consist of multiple decision-making agents that interact in a shared environment to achieve common or conflicting goals.

Critical infrastructures, such as smart grids, wireless sensor networks, multi-robot systems, etc., are typical examples of multi-agent systems that consist of large-scale physical processes which are monitored and controlled over a set of communication networks and computers.

Presents solutions to different resilient cooperative control and optimization problems of multi-agent systems

Includes a wealth of examples on attack-resilient consensus control, time-varying formation tracking control, distributed optimization and distributed Nash equilibrium game-seeking

Shows, in detail, the practicalities of how to develop an attack-resilient cooperative control and optimization framework