1st Edition
Control and State Estimation for Dynamical Network Systems with Complex Samplings
306 Pages
66 B/W Illustrations
by
CRC Press
306 Pages
66 B/W Illustrations
by
CRC Press
306 Pages
66 B/W Illustrations
by
CRC Press
Also available as eBook on:
This book focuses on the control and state estimation problems for dynamical network systems with complex samplings subject to various network-induced phenomena. It includes a series of control and state estimation problems tackled under the passive sampling fashion. Further, it explains the effects from the active sampling fashion, i.e., event-based sampling is examined on the control/estimation... Read more
1. Introduction 1.1. Background 1.2 Recent Advances 1.3 Outline 2. Stabilization and Control under Noisy Sampling Intervals 2.1 Stabilization with Single Input 2.2 Quantized/Saturated Control with Multiple Inputs 2.3 Illustrative Examples 2.4 Summary 3. Distributed State Estimation over Sensor Networks with Nonuniform Samplings 3.1 Problem Formulation 3.2 Main Results 3.3 An Illustrative Example 3.4 Summary 4. Event-Triggered Control for Switched Systems 4.1 Event-Triggered Control: The Input-to-State Stability 4.2 Event-Triggered Pinning Synchronization Control 4.3 Illustrative Examples 4.4 Summary 5. Event-Triggered H∞ State Estimation for State-Saturated Systems 5.1 Distributed Event-Triggered H∞ State Estimation in Sensor Networks 5.2 Event-Triggered H∞ State Estimation in Complex Networks 5.3 Illustrative Examples 5.4 Summary 6. Event-Triggered State Estimation for Discrete-Time Neural Networks 6.1 Event-Triggered State Estimation with Stochastic Parameters 6.2 Event-Triggered H∞ State Estimation in Genetic Regulatory Networks 6.3 Illustrative Examples 6.4 Summary 7. Event-Triggered Fusion Estimation for Multi-Rate Systems 7.1 Event-Triggered Fusion Estimation with Colored Measurement Noises 7.2 Event-Triggered Fusion Estimation with Sensor Degradations 7.3 Illustrative Examples 7.4 Summary 8. Synchronization Control under Dynamic Event-Triggered Mechanisms 8.1 Problem Formulation 8.2 Main Results 8.3 Illustrative Examples 8.4 Summary 9. Filtering or State Estimation under Dynamic Event-Triggered Mechanisms 9.1 Dynamic Event-Triggered Robust Filtering with Censored Measurements 9.2 Dynamic Event-Triggered Distributed Filtering on Gilbert-Elliott Channels 9.3 Dynamic Event-Triggered Resilient H∞ State Estimation 9.4 Illustrative Examples 9.5 Summary 10. Conclusions and Future Work
Biography
Bo Shen, Zidong Wang, Qi Li
