Description
Robust Integration of Model-Based Fault Estimation and Fault-Tolerant Control is a systematic examination of methods used to overcome the inevitable system uncertainties arising when a fault estimation (FE) function and a fault-tolerant controller interact as they are employed together to compensate for system faults and maintain robustly acceptable system performance. It covers the important subject of robust integration of FE and FTC with the aim of guaranteeing closed-loop stability. The reader's understanding of the theory is supported by the extensive use of tutorial examples, including some MATLAB(R)-based material available from the Springer website and by industrial-applications-based material.
The text is structured into three parts:
- Part I examines the basic concepts of FE and FTC, providing extensive insight into the importance of and challenges involved in their integration;
- Part II describes five effective strategiesfor the integration of FE and FTC: sequential, iterative, simultaneous, adaptive-decoupling, and robust decoupling; and
- Part III begins to extend the proposed strategies to nonlinear and large-scale systems and covers their application in the fields of renewable energy, robotics and networked systems.
The book is a useful resource for researchers and engineers working in the area of fault-tolerant control systems, and supplementary material for a graduate- or postgraduate-level course on fault diagnosis and FTC.
Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
About the Author
Dr Jianglin Lan received his B.Eng. degree in Automation from the South China Agricultural University in 2011, M.Sc. degree in Control Theory and Control Engineering from the South China University of Technology in 2014, and Ph.D. degree in Control & Intelligent Systems Engineering from the University of Hull in 2017. From August 2017 to November 2018, he was as a Research Associate in the Rolls-Royce University Technology Centre at the Department of Automatic Control and Systems Engineering, University of Sheffield. Since November 2018, he has been working as a Research Associate at the Department of Aeronautical and Automotive Engineering, Loughborough University. He is the author of 22 refereed papers (including 9 journal papers) and 1 chapter in an edited monograph. His research interests include fault estimation and fault-tolerant control, robust optimization and decision making, and their applications for renewable energy, robotics and network systems. ProfessorRon J. Patton graduated from Sheffield University with B.Eng., M.Eng., Ph.D. degrees in Electrical & Electronic Engineering and Control Systems. He holds the Chair in Control & Intelligent Systems Engineering at Hull University and has made a substantial contribution in over 35 years to the field of modelling Robust methods for FDI/FDD (fault detection and isolation/fault detection and diagnosis) and Fault-Tolerant Control (FTC) in dynamic systems. He has a Hirsch Index H_55 and is author of 490 papers, including 140 journal papers and 6 books. Dr Patton serves on the Editorial Board of the International Journal of Applied Mathematics and Computer Science. He is Subject Editor in System Supervision: Fault-tolerant Control & Diagnosis for the Wiley Journal of Adaptive Control & Signal Processing. He has chaired several conference committees including the International Programme Committees for IFAC Safeprocess'97, UKACC Control'98 and the Med'08. His current research interests are robust multiple-model and de-centralized strategies for FDI/FDD & FTC and Renewable Energy including load mitigation control for offshore wind turbines and wave to wire control of wave energy conversion. He is Fellow of IEEE, Senior member of AIAA and Fellow of the Institute of Measurement and Control.