Control and state estimation for dynamical network systems with complex samplings. (2022)

• Record Type: Book
• Further Information: Note: Bo Shen, Zidong Wang, Qi Li.
• Authors: Shen, Bo, 1981-; Wang, Zidong, 1966-; (Professor of information science and engineering), Li, Qi
• Contents: 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
• Edition: 1st
• Publisher Details: Boca Raton : CRC Press
• Publication Date: 2022
• Extent: 1 online resource, illustrations (black and white)
• Subjects: 629.836; Adaptive control systems; Sensor networks; Neural networks (Computer science); Parameter estimation; Observers (Control theory); Sampling (Statistics)
• Languages: English
• ISBNs: 9781000635478; 9781000635454; 9781003307648
• Related ISBNs: 9781032309965
• Notes: Note: Includes bibliographical references and index.; Note: Description based on CIP data; resource not viewed.
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