Control and State Estimation for Dynamical Network Systems with Complex Samplings

This book focusses 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, effects from the active sampling fashion with simulation results.

1. Introduction 2. Stabilization and Control under Noisy Sampling Intervals 3. Distributed State Estimation over Sensor Networks with Nonuniform Samplings 4. Event-Triggered Control for Switched Systems 5. Event-Triggered H- State Estimation for State-Saturated Systems 6. Event-Triggered State Estimation for Discrete-Time Neural Networks 7. Event-Triggered Fusion Estimation for Multi-Rate Systems 8. Synchronization Control under Dynamic Event-Triggered Mechanisms 9. Filtering or State Estimation under Dynamic Event-Triggered Mechanisms 10. Conclusions and Future Work