Dynamic Event-Triggered Fault Diagnosis, State Estimation, and Predictive Control for Networked Systems
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Dynamic Event-Triggered Fault Diagnosis, State Estimation, and Predictive Control for Networked Systems
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Dynamic Event-Triggered Fault Diagnosis, State Estimation, and Predictive Control for Networked Systems
Description
The four novel Dynamic Event-Triggered Mechanisms (DETMs) in this book are for complex networked systems that optimize resource utilization while preserving system performance. These include hybrid dynamic variables-dependent ETMs, hybrid adjusting variables-dependent ETMs, bounded dynamic variable/time-varying threshold-dependent ETMs, and terminal constraint set-dependent mixed time/event-triggered mechanisms. It explores applications across fault diagnosis in networked systems, finite-time state estimation for complex dynamical networks, and MPC implementation.
- Presents a systematic study on dynamic event-triggered mechanisms
- Reviews comprehensive research results on dynamic event-triggered fault diagnosis, state estimation, and MPC
- Explores how these theories can be applied to the practical engineering problem of load frequency control in power systems
- Discusses complex factors including cyber-attacks, multiple timescales, jumping system parameters, hard constraints, polytopic uncertainties, nonlinearities, and limited network/computing resources
- Includes numerous simulations and examples to validate the theoretical results including single-link rigid robot model systems, motor systems, and power systems.
This book is aimed at graduate students and researchers in control systems, computer sciences, and signal processing.
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