Description
Taylor and Francis Ltd State Estimation and Fault Diagnosis under Imperfect Measurements 1st Edition 2022 Hardbound by Liu, Yang
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.Features:Reviews latest research results on the state estimation and fault diagnosis issues.Presents comprehensive framework constituted for systems under imperfect measurements.Includes quantitative performance analyses to solve problems in practical situations.Provides simulation examples extracted from practical engineering scenarios.Discusses proper and novel techniques such as the Carleman approximation and completing the square method is employed to solve the mathematical problems.This book aims at Graduate students, Professionals and Researchers in Control Science and Application, Stochastic Process, Fault Diagnosis, and Instrumentation and Measurement. 1. Introduction2. Optimal Filtering for Networked Systems with Stochastic Sensor Gain Degradation3. Recursive Filtering over Sensor Networks with Stochastic Sensor Gain Degradation4. H Filtering for Nonlinear Systems with Stochastic Sensor Saturations and Markov Time-Delays5. Observer Design for Systems with Unknown Inputs and Missing Measurements6. Filtering and Fault Detection for Nonlinear Systems with Polynomial Approximation7. Event-triggered Filtering and Fault Estimation for Nonlinear Systems with Stochastic Sensor Saturations8. Finite-horizon Quantized H Filter Design for Time-Varying Systems under Event-Triggered Transmissions9. Observer-Based Fault Diagnosis Schemes under Closed-loop Control10. State Estimation and Fault Reconstruction with Integral Measurements under Partially Decoupled Disturbances11. Conclusion and Further Work