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The objective of this book is to present the up-to-date research developments and novel methodologies on state estimation and fault diagnosis (FD) techniques for a class of complex systems subject to closed-loop control, nonlinearities, and stochastic phenomena. It covers state estimation design methodologies and FD unit design methodologies including framework of optimal filter and FD unit design, robust filter and FD unit design, stability, and performance analysis for the considered systems subject to various kinds of complex factors.This book aims at Graduate students, Professionals and Researchers in Control Science and Application, Stochastic Process, Fault Diagnosis, and Instrumentation and Measurement.
Introduction
Optimal Filtering for Networked Systems with Stochastic Sensor Gain Degradation
Recursive Filtering over Sensor Networks with Stochastic Sensor Gain Degradation
H∞ Filtering for Nonlinear Systems with Stochastic Sensor Saturations and Markov Time Delays
Observer Design for Systems with Unknown Inputs and Missing Measurements
Filtering and Fault Detection for Nonlinear Systems with Polynomial Approximation
Event-Triggered Filtering and Fault Estimation for Nonlinear Systems with Stochastic Sensor Saturations
Finite-Horizon Quantized H∞ Filter Design for Time-Varying Systems under Event-Triggered Transmissions
Observer-Based Fault Diagnosis Schemes under Closed-Loop Control
State Estimation and Fault Reconstruction with Integral Measurements under Partially Decoupled Disturbances
Conclusion and Further Work