Performance Analysis and Synthesis for Discrete-Time Stochastic Systems with Network-Enhanced Complexities
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.
- 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
Table of 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.