Key Features
- Unifies existing and emerging concepts concerning stochastic control/filtering and distributed control/filtering with an emphasis on a variety of network-induced complexities
- Includes concepts like randomly occurring sensor failures and consensus in probability (with respect to time-varying stochastic multi-agent systems)
- Exploits the recursive linear matrix inequality approach, completing the square method, Hamilton-Jacobi inequality approach, and parameter-dependent matrix inequality approach to handle the emerging mathematical/computational challenges
- Captures recent advances of theories, techniques, and applications of stochastic control as well as filtering from an engineering-oriented perspective
- Gives simulation examples in each chapter to reflect the engineering practice
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