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Full Description
The book addresses the system performance with a focus on the network-enhanced complexities and developing the engineering-oriented design framework of controllers and filters with potential applications in system sciences, control engineering and signal processing areas. Therefore, it provides a unified treatment on the analysis and synthesis for discrete-time stochastic systems with guarantee of certain performances against network-enhanced complexities with applications in sensor networks and mobile robotics. Such a result will be of great importance in the development of novel control and filtering theories including industrial impact.
Key Features
Provides original methodologies and emerging concepts to deal with latest issues in the control and filtering with an emphasis on a variety of network-enhanced complexities
Gives results of stochastic control and filtering distributed control and filtering, and security control of complex networked systems
Captures the essence of performance analysis and synthesis for stochastic control and filtering
Concepts and performance indexes proposed reflect the requirements of engineering practice
Methodologies developed in this book include backward recursive Riccati difference equation approach and the discrete-time version of input-to-state stability in probability
Contents
1 Introduction. 2 Finite-Horizon H∞ Control with Randomly Occurring Non-linearities and Fading Measurements. 3. Finite-Horizon H∞ Consensus Control for Multi-Agent Systems with Missing Measurements. 4 Finite-Horizon Distributed H∞ State Estimation with Stochastic Parameters through Sensor Networks. 5 Finite-Horizon Dissipative Control for State-Saturated Discrete Time-Varying Systems with Missing Measurements. 6 Finite-Horizon H∞ Filtering for State-Saturated Discrete Time-Varying Systems with Packet Dropouts. 7 Finite-Horizon Envelope-Constrained H∞ Filtering with Fading Measurements. 8 Distributed Filtering under Uniform Quantizations and Deception Attacks through Sensor Networks. 9 Event-Triggered Distributed H∞ State Estimation with Packet Dropouts through Sensor Networks. 10 Event-Triggered Consensus Control for Multi-Agent Systems in the Framework of Input-to-State Stability in Probability. 11 Event-Triggered Security Control for Discrete-Time Stochastic Systems subject to Cyber-Attacks. 12 Event-Triggered Consensus Control for Multi-Agent Systems subject to Cyber-Attacks in the Framework of Observers.
