In this book control and filtering problems for several classes of stochastic networked systems are discussed. In each chapter the stability robustness reliability consensus performance and/or disturbance attenuation levels are investigated within a unified theoretical framework. The aim is to derive the sufficient conditions such that the resulting systems achieve the prescribed design requirements despite all the network-induced phenomena. Further novel notions such as randomly occurring sensor failures and consensus in probability are discussed. Finally the theories/techniques developed are applied to emerging research areas. 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 . Language: English