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Robust Observer-Based Fault Diagnosis for Nonlinear Systems Using MATLAB®
Springer | Control Engineering | May 29 2016 | ISBN-10: 3319323237 | 224 pages | pdf | 11.9 mb

Authors: Zhang, Jian, Swain, Akshya Kumar, Nguang, Sing Kiong
Serves as a self-contained treatment with detailed proofs, allowing readers to easily understand the use of robust observers in fault diagnosis
Presents industrial applications in a real-world context, with examples of systems, including satellites, robot arms and aircraft
Offers MATLAB® and Simulink® files for download, which will aid the reader in reproducing and assimilating examples and methods
This book introduces several observer-based methods, including:
• the sliding-mode observer
• the adaptive observer
• the unknown-input observer and
• the descriptor observer method
for the problem of fault detection, isolation and estimation, allowing readers to compare and contrast the different approaches. The authors present basic material on Lyapunov stability theory, H¥ control theory, sliding-mode control theory and linear matrix inequality problems in a self-contained and step-by-step manner. Detailed and rigorous mathematical proofs are provided for all the results developed in the text so that readers can quickly gain a good understanding of the material. MATLAB® and Simulink® codes for all the examples, which can be downloaded from http://extras.springer.com, enable students to follow the methods and illustrative examples easily. The systems used in the examples make the book highly relevant to real-world problems in industrial control engineering and include a seventh-order aircraft model, a single-link flexible joint robot arm and a satellite controller. To help readers quickly find the information they need and to improve readability, the individual chapters are written so as to be semi-independent of each other.
Robust Oberserver-Based Fault Diagnosis for Nonlinear Systems Using MATLAB® is of interest to process, aerospace, robotics and control engineers, engineering students and researchers with a control engineering background.
Number of Illustrations and Tables
2 b/w illustrations, 42 illustrations in colour
Topics
Control
Industrial Chemistry / Chemical Engineering
Aerospace Technology and Astronautics
Robotics and Automation
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