Robust Observer-Based Fault Diagnosis for Nonlinear Systems Using MATLAB®

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Publisher : Springer
ISBN 13 : 3319323245
Total Pages : 231 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Robust Observer-Based Fault Diagnosis for Nonlinear Systems Using MATLAB® by : Jian Zhang

Download or read book Robust Observer-Based Fault Diagnosis for Nonlinear Systems Using MATLAB® written by Jian Zhang and published by Springer. This book was released on 2016-05-27 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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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Publisher :
ISBN 13 :
Total Pages : 176 pages
Book Rating : 4.:/5 (83 download)

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Book Synopsis Robust Observer Based Fault Diagnosis for Nonlinear Systems by : Jian Zhang

Download or read book Robust Observer Based Fault Diagnosis for Nonlinear Systems written by Jian Zhang and published by . This book was released on 2013 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Fuzzy Observer Based Fault Detection for Nonlinear Systems

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Publisher :
ISBN 13 :
Total Pages : 101 pages
Book Rating : 4.:/5 (183 download)

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Book Synopsis Robust Fuzzy Observer Based Fault Detection for Nonlinear Systems by : Magdy G. M. el- Ghatwary

Download or read book Robust Fuzzy Observer Based Fault Detection for Nonlinear Systems written by Magdy G. M. el- Ghatwary and published by . This book was released on 2007 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Model-Based Fault Diagnosis

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Publisher : Springer Nature
ISBN 13 : 9811967067
Total Pages : 207 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Model-Based Fault Diagnosis by : Zhenhua Wang

Download or read book Model-Based Fault Diagnosis written by Zhenhua Wang and published by Springer Nature. This book was released on 2022-10-28 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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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Publisher : Springer Nature
ISBN 13 : 981158155X
Total Pages : 5416 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Advances in Guidance, Navigation and Control by : Liang Yan

Download or read book Advances in Guidance, Navigation and Control written by Liang Yan and published by Springer Nature. This book was released on 2021-11-12 with total page 5416 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Robust Integration of Model-Based Fault Estimation and Fault-Tolerant Control

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Publisher : Springer Nature
ISBN 13 : 3030587606
Total Pages : 275 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Robust Integration of Model-Based Fault Estimation and Fault-Tolerant Control by : Jianglin Lan

Download or read book Robust Integration of Model-Based Fault Estimation and Fault-Tolerant Control written by Jianglin Lan and published by Springer Nature. This book was released on 2020-12-11 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Advances in Data Science and Computing Technologies

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Publisher : Springer Nature
ISBN 13 : 981993656X
Total Pages : 738 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Advances in Data Science and Computing Technologies by : Basabi Chakraborty

Download or read book Advances in Data Science and Computing Technologies written by Basabi Chakraborty and published by Springer Nature. This book was released on 2023-09-29 with total page 738 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Smart Embedded Systems

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Publisher : CRC Press
ISBN 13 : 1003810268
Total Pages : 300 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Smart Embedded Systems by : Arun Sinha

Download or read book Smart Embedded Systems written by Arun Sinha and published by CRC Press. This book was released on 2023-12-01 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Smart Embedded Systems: Advances and Applications" is a comprehensive guide that demystifies the complex world of embedded technology. The book journeys through a wide range of topics from healthcare to energy management, autonomous robotics, and wireless communication, showcasing the transformative potential of intelligent embedded systems in these fields. This concise volume introduces readers to innovative techniques and their practical applications, offers a comparative analysis of wireless protocols, and provides efficient resource allocation strategies in IoT-based ecosystems. With real-world examples and in-depth case studies, it serves as an invaluable resource for students and professionals seeking to harness the power of embedded technology to shape our digital future. Salient Features: The book provides a comprehensive coverage of various aspects of smart embedded systems, exploring their design, implementation, optimization, and a range of applications. This is further enhanced by in-depth discussions on hardware and software optimizations aimed at improving overall system performance. A detailed examination of machine learning techniques specifically tailored for data analysis and prediction within embedded systems. This complements the exploration of cutting-edge research on the use of AI to enhance wireless communications. Real-world applications of these technologies are extensively discussed, with a focus on areas such as seizure detection, noise reduction, health monitoring, diabetic care, autonomous vehicles, and communication systems. This includes a deep-dive into different wireless protocols utilized for data transfer in IoT systems. This book highlights key IoT technologies and their myriad applications, extending from environmental data collection to health monitoring. This is underscored by case studies on the integration of AI and IoT in healthcare, spanning topics from anomaly detection to informed clinical decision-making. Also featured is a detailed evaluation and comparison of different system implementations and methodologies This book is an essential read for anyone interested in the field of embedded systems. Whether you're a student looking to broaden your knowledge base, researchers looking in-depth insights, or professionals planning to use this cutting-edge technology in real-world applications, this book offers a thorough grounding in the subject.

Robust Fault Diagnosis in Linear and Nonlinear Systems Based on Unknown Input, and Sliding Mode Functional Observer Methodologies

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (654 download)

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Book Synopsis Robust Fault Diagnosis in Linear and Nonlinear Systems Based on Unknown Input, and Sliding Mode Functional Observer Methodologies by :

Download or read book Robust Fault Diagnosis in Linear and Nonlinear Systems Based on Unknown Input, and Sliding Mode Functional Observer Methodologies written by and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Knowledge-Based Intelligent System Advancements: Systemic and Cybernetic Approaches

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Publisher : IGI Global
ISBN 13 : 1616928131
Total Pages : 506 pages
Book Rating : 4.6/5 (169 download)

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Book Synopsis Knowledge-Based Intelligent System Advancements: Systemic and Cybernetic Approaches by : Jozefczyk, Jerzy

Download or read book Knowledge-Based Intelligent System Advancements: Systemic and Cybernetic Approaches written by Jozefczyk, Jerzy and published by IGI Global. This book was released on 2010-08-31 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge-Based Intelligent System Advancements: Systemic and Cybernetic Approaches presents selected new AI–based ideas and methods for analysis and decision making in intelligent information systems derived using systemic and cybernetic approaches. This book is useful for researchers, practitioners and students interested intelligent information retrieval and processing, machine learning and adaptation, knowledge discovery, applications of fuzzy based methods and neural networks.

Model Based Fault Diagnosis in Complex Control Systems

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Publisher :
ISBN 13 :
Total Pages : 460 pages
Book Rating : 4.:/5 (112 download)

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Book Synopsis Model Based Fault Diagnosis in Complex Control Systems by : Weitian Chen

Download or read book Model Based Fault Diagnosis in Complex Control Systems written by Weitian Chen and published by . This book was released on 2007 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Fault Detection and Diagnosis in Nonlinear Systems

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Publisher : Springer
ISBN 13 : 3319030477
Total Pages : 143 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Fault Detection and Diagnosis in Nonlinear Systems by : Rafael Martinez-Guerra

Download or read book Fault Detection and Diagnosis in Nonlinear Systems written by Rafael Martinez-Guerra and published by Springer. This book was released on 2013-11-19 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: The high reliability required in industrial processes has created the necessity of detecting abnormal conditions, called faults, while processes are operating. The term fault generically refers to any type of process degradation, or degradation in equipment performance because of changes in the process's physical characteristics, process inputs or environmental conditions. This book is about the fundamentals of fault detection and diagnosis in a variety of nonlinear systems which are represented by ordinary differential equations. The fault detection problem is approached from a differential algebraic viewpoint, using residual generators based upon high-gain nonlinear auxiliary systems (‘observers’). A prominent role is played by the type of mathematical tools that will be used, requiring knowledge of differential algebra and differential equations. Specific theorems tailored to the needs of the problem-solving procedures are developed and proved. Applications to real-world problems, both with constant and time-varying faults, are made throughout the book and include electromechanical positioning systems, the Continuous Stirred Tank Reactor (CSTR), bioreactor models and belt drive systems, to name but a few.

Robust Fault Diagnosis in Linear and Nonlinear Systems Based on Unknown Input, and Sliding Mode Functional Observer Methodologies [microform]

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Publisher : National Library of Canada = Bibliothèque nationale du Canada
ISBN 13 : 9780612616967
Total Pages : 380 pages
Book Rating : 4.6/5 (169 download)

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Book Synopsis Robust Fault Diagnosis in Linear and Nonlinear Systems Based on Unknown Input, and Sliding Mode Functional Observer Methodologies [microform] by : Yi Xiong

Download or read book Robust Fault Diagnosis in Linear and Nonlinear Systems Based on Unknown Input, and Sliding Mode Functional Observer Methodologies [microform] written by Yi Xiong and published by National Library of Canada = Bibliothèque nationale du Canada. This book was released on 2001 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Fault Diagnosis in Nonlinear Systems Using Learning and Sliding Mode Approaches with Applications for Satellite Control Systems

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Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (112 download)

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Book Synopsis Fault Diagnosis in Nonlinear Systems Using Learning and Sliding Mode Approaches with Applications for Satellite Control Systems by : Qing Wu

Download or read book Fault Diagnosis in Nonlinear Systems Using Learning and Sliding Mode Approaches with Applications for Satellite Control Systems written by Qing Wu and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems

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Publisher : Springer Science & Business Media
ISBN 13 : 3540711163
Total Pages : 214 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems by : Marcin Witczak

Download or read book Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems written by Marcin Witczak and published by Springer Science & Business Media. This book was released on 2007-07-08 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph presents a variety of techniques that can be used for designing robust fault diagnosis schemes for non-linear systems. The introductory part of the book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. Subsequently, advanced robust observer structures are presented. Parameter estimation based techniques are discussed as well. A particular attention is drawn to experimental design for fault diagnosis. The book also presents a number of robust soft computing approaches utilizing evolutionary algorithms and neural networks. All approaches described in this book are illustrated by practical applications.

Dynamic Surface Control of Uncertain Nonlinear Systems

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Publisher : Springer Science & Business Media
ISBN 13 : 0857296329
Total Pages : 257 pages
Book Rating : 4.8/5 (572 download)

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Book Synopsis Dynamic Surface Control of Uncertain Nonlinear Systems by : Bongsob Song

Download or read book Dynamic Surface Control of Uncertain Nonlinear Systems written by Bongsob Song and published by Springer Science & Business Media. This book was released on 2011-05-16 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the problem of nonlinear controller design is as old as that of linear controller design, the systematic design methods framed in response are more sparse. Given the range and complexity of nonlinear systems, effective new methods of control design are therefore of significant importance. Dynamic Surface Control of Uncertain Nonlinear Systems provides a theoretically rigorous and practical introduction to nonlinear control design. The convex optimization approach applied to good effect in linear systems is extended to the nonlinear case using the new dynamic surface control (DSC) algorithm developed by the authors. A variety of problems – DSC design, output feedback, input saturation and fault-tolerant control among them – are considered. The inclusion of applications material demonstrates the real significance of the DSC algorithm, which is robust and easy to use, for nonlinear systems with uncertainty in automotive and robotics. Written for the researcher and graduate student of nonlinear control theory, this book will provide the applied mathematician and engineer alike with a set of powerful tools for nonlinear control design. It will also be of interest to practitioners working with a mechatronic systems in aerospace, manufacturing and automotive and robotics, milieux.

Observer-based Fault Detection in Nonlinear Systems

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Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (17 download)

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Book Synopsis Observer-based Fault Detection in Nonlinear Systems by : Abdul Qayyum Khan

Download or read book Observer-based Fault Detection in Nonlinear Systems written by Abdul Qayyum Khan and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: