Robust Observer Based Fault Diagnosis For Nonlinear Systems Using Matlab
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Robust Observer Based Fault Diagnosis For Nonlinear Systems Using Matlab
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Author : Jian Zhang
language : en
Publisher: Springer
Release Date : 2016-05-27
Robust Observer Based Fault Diagnosis For Nonlinear Systems Using Matlab written by Jian Zhang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-27 with Technology & Engineering categories.
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.
Robust Observer Based Fault Diagnosis For Nonlinear Systems
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Author : Jian Zhang
language : en
Publisher:
Release Date : 2013
Robust Observer Based Fault Diagnosis For Nonlinear Systems written by Jian Zhang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Electric fault location categories.
The field of observer based fault diagnosis for nonlinear systems has become an important topic of research in the control community over the last three decades. In this thesis, the issues of robust fault detection, isolation and estimation of actuator faults and sensor faults for Lipschitz nonlinear systems has been studied using sliding mode, adaptive and descriptor system approaches. The problem of estimating actuator faults is initially discussed. The sliding mode observer (SMO) is constructed directly based on the uncertain nonlinear system. The fault is reconstructed using the concept of equivalent output injection. Sensor faults are treated as actuator faults by using integral observer based approach and then the problem of sensor fault diagnosis, including detection, isolation and estimation is studied. The proposed scheme has the ability of successfully diagnosing incipient sensor faults in the presence of system uncertainties. The results are then extended to simultaneously estimate actuator faults and sensor faults using SMOs, adaptive observers (AO) and descriptor system approaches. H_ filtering is integrated into the observers to ensure that the fault estimation error as well as the state estimation error are less than a prescribed performance level. The existence of the proposed fault estimators and their stability analysis are carried out in terms of LMIs. It has been observed that when the Lipschitz constant is unknown or too large, it may fail to find feasible solutions for observers. In order to deal with this situation, adaptation laws are used to generate an additional control input to the nonlinear system. The additional control input can eliminate the effect of Lipschitz constant on the solvability of LMIs. The effectiveness of various methods proposed in this research has been demonstrated using several numerical and practical examples. The simulation results demonstrate that the proposed methods can achieve the prescribed performance requirements.
Robust Integration Of Model Based Fault Estimation And Fault Tolerant Control
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Author : Jianglin Lan
language : en
Publisher: Springer Nature
Release Date : 2020-12-11
Robust Integration Of Model Based Fault Estimation And Fault Tolerant Control written by Jianglin Lan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-11 with Technology & Engineering categories.
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®-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 strategies for 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 strategies presented are applicable to a broad range of control problems, because in the absence of faults the FE-based FTC naturally reverts to conventional observer-based control. 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.
Robust Fuzzy Observer Based Fault Detection For Nonlinear Systems
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Author : Magdy G. M. el- Ghatwary
language : en
Publisher:
Release Date : 2007
Robust Fuzzy Observer Based Fault Detection For Nonlinear Systems written by Magdy G. M. el- Ghatwary and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
Model Based Fault Diagnosis In Complex Control Systems
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Author : Weitian Chen
language : en
Publisher:
Release Date : 2007
Model Based Fault Diagnosis In Complex Control Systems written by Weitian Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Failure analysis (Engineering) categories.
This thesis deals with model based fault diagnosis problems for several classes of systems with complexities such as uncertainties and nonlinearities. To deal with system complexities, robust and adaptive approaches are used as the main tools. To focus more on fault isolation and estimation, novel observer and output estimator based fault diagnosis schemes are proposed. Chapters 2 to 4 employ robust approaches to deal with complexities such as nonlinearities and nonparametric uncertainties. Robust observers, that is, Unknown Input Observers (UIOs) and Sliding Mode Observers (SMOs), are designed to solve fault diagnosis problems for Lipschitz nonlinear systems and Takagi-Sugeno fuzzy system represented uncertain nonlinear systems. UIO and SMO based fault diagnosis schemes, whose main novelty lies in the fault isolation, are proposed. Chapters 5 and 6 also use robust approaches to attack more challenging complexities such as unmatched uncertainties. A novel idea which advocates output estimator design and abandons the state observer design is proposed. Robust output estimator based fault diagnosis schemes are developed for a class of linear systems with both matched and unmatched non-parametric uncertainties. The output estimator approach is extended to a more general class of linear systems, and a high-order sliding mode differentiator based actuator fault diagnosis scheme is designed, which is the first in fault diagnosis. Chapters 7 and 8 use adaptive approaches to cope with complexities such as parametric uncertainties. Adaptive output estimator based fault diagnosis schemes are designed for sensor and actuator fault diagnosis problems in unknown linear Multi-Input Multi-Output (MIMO) and Multi-Input Single-Output (MISO) systems. A novel idea involving integration of fault isolation design functions into controller designs is put forward in actuator fault diagnosis. The results in this thesis demonstrate that: 1) the proposed robust observer based fault diagnosis schemes are powerful in dealing with matched uncertainties and certain types of nonlinearities; 2) the proposed robust output estimator (and output derivative estimator) based fault diagnosis schemes are powerful in counteracting unmatched non-parametric uncertainties; and 3) the adaptive output estimator approach is very promising and powerful in coping with parametric uncertainties. The thesis concludes by discussing important open problems for future research.
Model Based Fault Diagnosis
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Author : Zhenhua Wang
language : en
Publisher: Springer Nature
Release Date : 2022-10-28
Model Based Fault Diagnosis written by Zhenhua Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-28 with Technology & Engineering categories.
This book investigates in detail model-based fault diagnosis methods, including observer-based residual generation, residual evaluation based on threshold computation, observer-based fault isolation strategies, observer-based fault estimation, Kalman filter-based fault diagnosis methods, and parity space approach. Studies on model-based fault diagnosis have attracted engineers and scientists from various disciplines, such as electrical, aerospace, mechanical, and chemical engineering. Pursuing a holistic approach, the book establishes a fundamental framework for this topic, while emphasizing the importance of state-space approach. The methods introduced in the book are systemic and easy to follow. The book is intended for undergraduate and graduate students who are interested in fault diagnosis and state estimation, researchers investigating fault diagnosis and fault-tolerant control, and control system design engineers working on safety-critical systems.
Advances In Guidance Navigation And Control
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Author : Liang Yan
language : en
Publisher: Springer Nature
Release Date : 2021-11-12
Advances In Guidance Navigation And Control written by Liang Yan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-12 with Technology & Engineering categories.
This book features the latest theoretical results and techniques in the field of guidance, navigation, and control (GNC) of vehicles and aircraft. It covers a range of topics, including, but not limited to, intelligent computing communication and control; new methods of navigation, estimation, and tracking; control of multiple moving objects; manned and autonomous unmanned systems; guidance, navigation, and control of miniature aircraft; and sensor systems for guidance, navigation, and control. Presenting recent advances in the form of illustrations, tables, and text, it also provides detailed information of a number of the studies, to offer readers insights for their own research. In addition, the book addresses fundamental concepts and studies in the development of GNC, making it a valuable resource for both beginners and researchers wanting to further their understanding of guidance, navigation, and control.
Fault Diagnosis In Nonlinear Systems Using Learning And Sliding Mode Approaches With Applications For Satellite Control Systems
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Author : Qing Wu
language : en
Publisher:
Release Date : 2008
Fault Diagnosis In Nonlinear Systems Using Learning And Sliding Mode Approaches With Applications For Satellite Control Systems written by Qing Wu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Fault location (Engineering) categories.
In this thesis, model based fault detection, isolation, and estimation problem in several classes of nonlinear systems is studied using sliding mode and learning approaches. First, a fault diagnosis scheme using a bank of repetitive learning observers is presented. The diagnostic observers are established in a generalized observer scheme, and the observer inputs are repetitively updated using the output estimation error in a proportional-integral structure. Next, a framework for robust fault diagnosis using sliding mode and learning approaches is proposed to deal with various types of faults in a class of nonlinear systems with triangular input form. In the designed diagnostic observers, first order and second order sliding modes are used respectively, to achieve robust state estimation in the presence of uncertainties, and additional online estimators are established to characterize the faults. In order to guarantee that the sliding mode is able to distinguish the system uncertainties from the faults, two iterative adaptive laws are used to update the sliding mode switching gains. Moreover, different online fault estimators are developed using neural state space models, iterative learning algorithms, and wavelet networks. Another class of nonlinear systems where an unmeasurable part of state can be described as a nonlinear function of the output and its derivatives is considered next. Accordingly, a class of fault diagnosis schemes using high order sliding mode differentiators (HOSMDs) and online estimators are proposed, where neural adaptive estimators and iterative neuron PID estimators are designed. Additionally, a fault diagnosis scheme using HOSMDs and neural networks based uncertainty observers is designed in order to achieve a better performance in robust fault detection. If the uncertainties can be accurately estimated, the generated diagnostic residual is more sensitive to the onset of faults. Finally, a fault diagnosis scheme using Takagi-Sugeno (TS) fuzzy models, neural networks, and sliding mode is developed. The availability of TS fuzzy models makes this fault diagnosis scheme applicable to a wider class of nonlinear systems. The proposed fault diagnosis schemes are applied to several types of satellite control systems, and the simulation results demonstrate their performance.
Advances In Data Science And Computing Technologies
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Author : Basabi Chakraborty
language : en
Publisher: Springer Nature
Release Date : 2023-09-29
Advances In Data Science And Computing Technologies written by Basabi Chakraborty and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-29 with Technology & Engineering categories.
This book presents selected research papers on current developments in artificial intelligence (AI) and data sciences from the International Conference on Advances in Data Science and Computing Technologies, ADSC 2022. The book covers topics such as soft computing techniques, AI, optical communication systems, application of Internet of Things, hybrid and renewable energy sources, cloud and mobile computing, deep machine learning, data networks & securities. The book discusses various aspects of these topics, e.g., technological considerations, product implementation, and application issues. The volume will serve as a reference resource for researchers and practitioners in academia and industry.
Robust Fault Diagnosis In Linear And Nonlinear Systems Based On Unknown Input And Sliding Mode Functional Observer Methodologies
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Author :
language : en
Publisher:
Release Date : 2001
Robust Fault Diagnosis In Linear And Nonlinear Systems Based On Unknown Input And Sliding Mode Functional Observer Methodologies written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with categories.