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Control and Filtering of Fuzzy Systems with Switched Parameters

Author: Shanling Dong

Publisher: Springer Nature

Published: 2019-11-25

Total Pages: 220

ISBN-13: 3030355667

This book presents recent advances in control and filter design for Takagi-Sugeno (T-S) fuzzy systems with switched parameters. Thanks to its powerful ability in transforming complicated nonlinear systems into a set of linear subsystems, the T-S fuzzy model has received considerable attention from those the field of control science and engineering. Typical applications of T-S fuzzy systems include communication networks, and mechanical and power electronics systems. Practical systems often experience abrupt variations in their parameters or structures due to outside disturbances or component failures, and random switching mechanisms have been used to model these stochastic changes, such as the Markov jump principle. There are three general types of controller/filter for fuzzy Markov jump systems: mode-independent, mode-dependent and asynchronous. Mode-independence does not focus on whether modes are accessible and ignores partially useful mode information, which results in some conservatism. The mode-dependent design approach relies on timely, complete and correct information regarding the mode of the studied plant. Factors like component failures and data dropouts often make it difficult to obtain exact mode messages, which further make the mode-dependent controllers/filters less useful. Recently, to overcome these issues, researchers have focused on asynchronous techniques. Asynchronous modes are accessed by observing the original systems based on certain probabilities. The book investigates the problems associated with controller/filter design for all three types. It also considers various networked constraints, such as data dropouts and time delays, and analyzes the performances of the systems based on Lyapunov function and matrix inequality techniques, including the stochastic stability, dissipativity, and $H_\infty$. The book not only shows how these approaches solve the control and filtering problems effectively, but also offers potential meaningful research directions and ideas. Covering a variety of fields, including continuous-time and discrete-time Markov processes, fuzzy systems, robust control, and filter design problems, the book is primarily intended for researchers in system and control theory, and is also a valuable reference resource for graduate and undergraduate students. Further, it provides cases of fuzzy control problems that are of interest to scientists, engineers and researchers in the field of intelligent control. Lastly it is useful for advanced courses focusing on fuzzy modeling, analysis, and control.

Intelligent Control, Filtering and Model Reduction Analysis for Fuzzy-Model-Based Systems

Author: Xiaojie Su

Publisher: Springer Nature

Published: 2021-08-17

Total Pages: 322

ISBN-13: 3030812146

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This book aims to introduce the state-of-the-art research of stability/performance analysis and optimal synthesis methods for fuzzy-model-based systems. A series of problems are solved with new approaches of design, analysis and synthesis of fuzzy systems, including stabilization control and stability analysis, dynamic output feedback control, fault detection filter design, and reduced-order model approximation. Some efficient techniques, such as Lyapunov stability theory, linear matrix inequality, reciprocally convex approach, and cone complementary linearization method, are utilized in the approaches. This book is a comprehensive reference for researchers and practitioners working on intelligent control, model reduction, and fault detection of fuzzy systems, and is also a useful source of information for senior undergraduates and graduates in these areas. The readers will benefit from some new concepts and methodologies with theoretical and practical significance in system analysis and control synthesis.

Control and Filtering of Fuzzy Systems Under Communication Channels

Author: Xiao-Heng Chang

Publisher: Springer Nature

Published: 2023-12-02

Total Pages: 257

ISBN-13: 9819943469

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This book systematically studies the feedback control and filtering problems for nonlinear plants with limited communication channels based on T-S fuzzy models. By fully considering different network-induced phenomena, such as signal quantizations, time-delays, data packet dropouts, communication protocols, cyber attacks, and so on, some significant strategies are provided for various performance analysis and different controller/filter synthesis of fuzzy systems. The event-triggered mechanism is also mentioned to save the communication resource. Moreover, some results are extended to the fault detection and fault-tolerant control. The book provides some new methodologies in analysis and synthesis of fuzzy systems under communication channels, and can serve as a valuable reference material for researchers wishing to explore the area of control and filtering of fuzzy systems and networked systems.

Fuzzy Control and Filter Design for Uncertain Fuzzy Systems

Author: Wudhichai Assawinchaichote

Publisher: Springer

Published: 2007-07-14

Total Pages: 180

ISBN-13: 3540370129

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Most real physical systems are nonlinear in nature. Control and ?ltering of nonlinear systems are still open problems due to their complexity natures. These problem becomes more complex when the system’s parameters are - certain. A common approach to designing a controller/?lter for an uncertain nonlinear system is to linearize the system about an operating point, and uses linear control theory to design a controller/?lter. This approach is successful when the operating point of the system is restricted to a certain region. H- ever, when a wide range operation of the system is required, this method may fail. ThisbookpresentsnewnovelmethodologiesfordesigningrobustH fuzzy ? controllers and robustH fuzzy ?lters for a class of uncertain fuzzy systems ? (UFSs), uncertain fuzzy Markovian jump systems (UFMJSs), uncertain fuzzy singularly perturbed systems (UFSPSs) and uncertain fuzzy singularly p- turbed systems with Markovian jumps (UFSPS–MJs). These new meth- ologies provide a framework for designing robustH fuzzy controllers and ? robustH fuzzy ?lters for these classes of systems based on a Tagaki-Sugeno ? (TS) fuzzy model. Solutions to the design problems are presented in terms of linear matrix inequalities (LMIs). To investigate the design problems, we ?rst describe a class of uncertain nonlinear systems (UNSs), uncertain nonlinear Markovianjumpsystems(UNMJSs),uncertainnonlinearsingularlyperturbed systems(UNSPSs)anduncertainnonlinearsingularlyperturbedsystemswith Markovian jumps (UNSPS–MJs) by a TS fuzzy system with parametric - certainties and with/without Markovian jumps. Then, based on an LMI - proach, we develop a technique for designing robustH fuzzy controllers and ? robustH fuzzy ?lters such that a given prescribed performance index is ? guaranteed.

Fuzzy Logic

Author: Elmer Dadios

Publisher: BoD – Books on Demand

Published: 2012-03-28

Total Pages: 432

ISBN-13: 9535103962

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This book introduces new concepts and theories of Fuzzy Logic Control for the application and development of robotics and intelligent machines. The book consists of nineteen chapters categorized into 1) Robotics and Electrical Machines 2) Intelligent Control Systems with various applications, and 3) New Fuzzy Logic Concepts and Theories. The intended readers of this book are engineers, researchers, and graduate students interested in fuzzy logic control systems.

Analysis and Synthesis of Fuzzy Control Systems

Author: Gang Feng

Publisher: CRC Press

Published: 2018-09-03

Total Pages: 299

ISBN-13: 1420092650

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Fuzzy logic control (FLC) has proven to be a popular control methodology for many complex systems in industry, and is often used with great success as an alternative to conventional control techniques. However, because it is fundamentally model free, conventional FLC suffers from a lack of tools for systematic stability analysis and controller design. To address this problem, many model-based fuzzy control approaches have been developed, with the fuzzy dynamic model or the Takagi and Sugeno (T–S) fuzzy model-based approaches receiving the greatest attention. Analysis and Synthesis of Fuzzy Control Systems: A Model-Based Approach offers a unique reference devoted to the systematic analysis and synthesis of model-based fuzzy control systems. After giving a brief review of the varieties of FLC, including the T–S fuzzy model-based control, it fully explains the fundamental concepts of fuzzy sets, fuzzy logic, and fuzzy systems. This enables the book to be self-contained and provides a basis for later chapters, which cover: T–S fuzzy modeling and identification via nonlinear models or data Stability analysis of T–S fuzzy systems Stabilization controller synthesis as well as robust H∞ and observer and output feedback controller synthesis Robust controller synthesis of uncertain T–S fuzzy systems Time-delay T–S fuzzy systems Fuzzy model predictive control Robust fuzzy filtering Adaptive control of T–S fuzzy systems A reference for scientists and engineers in systems and control, the book also serves the needs of graduate students exploring fuzzy logic control. It readily demonstrates that conventional control technology and fuzzy logic control can be elegantly combined and further developed so that disadvantages of conventional FLC can be avoided and the horizon of conventional control technology greatly extended. Many chapters feature application simulation examples and practical numerical examples based on MATLAB®.

Fuzzy Modeling and Fuzzy Control

Author: Huaguang Zhang

Publisher: Springer Science & Business Media

Published: 2007-10-17

Total Pages: 423

ISBN-13: 081764539X

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Fuzzy logic methodology has proven effective in dealing with complex nonlinear systems containing uncertainties that are otherwise difficult to model. Technology based on this methodology is applicable to many real-world problems, especially in the area of consumer products. This book presents the first comprehensive, unified treatment of fuzzy modeling and fuzzy control, providing tools for the control of complex nonlinear systems. Coverage includes model complexity, model precision, and computing time. This is an excellent reference for electrical, computer, chemical, industrial, civil, manufacturing, mechanical and aeronautical engineers, and also useful for graduate courses in electrical engineering, computer engineering, and computer science.

Adaptive Fuzzy Systems and Control

Author: Li-Xin Wang

Publisher: Prentice Hall

Published: 1994

Total Pages: 262

ISBN-13:

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This volume develops a variety of adaptive fuzzy systems and applies them to a variety of engineering problems. It summarizes the state-of-the-art methods for automatic tuning of the parameters and structures of fuzzy logic systems.

New Applications and Developments of Fuzzy Systems

Author: Ibrahim A. Hameed

Publisher: GRIN Verlag

Published: 2012-03-19

Total Pages: 105

ISBN-13: 3656152934

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Doctoral Thesis / Dissertation from the year 2010 in the subject Computer Sciences - Artificial Intelligence, grade: PhD, Korea University, Seoul (College of Engineering - Dept of Industrial Systems and Information Engineering), course: Intelligence Control and Artificial Intelligence, language: English, abstract: Fuzzy Logic (FL) is a particular area of interest in the study of Artificial intelligence (AI) based on the idea that in fuzzy sets each element in the set can assume a value from 0 to 1, not just 0 or 1, as in classic or crisp set theory. The gradation in the extent to which an element is belonging to the relevant sets is called the degree of membership. This degree of membership is a measure of the element's belonging to the set, and thus of the precision with which it explains the phenomenon being evaluated. A linguistic expression is given to each fuzzy set. The information contents of the fuzzy rules are then used to infer the output using a suitable inference engine. The key contribution of fuzzy logic in computation of information described in natural language made it applicable to a variety of applications and problem domains; from simple control systems to human decision support systems. Yet, despite its long-standing origins, it is a relatively new field, and as such leaves much room for development. The thesis presents two novel applications of fuzzy systems; a human decision support system to help teachers to fairly evaluate students and two hybrid intelligent fuzzy systems; a type-2 fuzzy logic system and a combined type-1 fuzzy logic system and extended Kalamn filter for controlling systems operating under high levels of uncertainties due to various sources of measurement and modeling errors. The combination of fuzzy logic and the classical student evaluation approach produces easy to understand transparent decision model that can be easily understood by students and teachers alike. The developed architecture overcomes the problem of ranking

Fuzzy Modeling and Control: Theory and Applications

Author: Fernando Matía

Publisher: Springer

Published: 2014-08-14

Total Pages: 291

ISBN-13: 9462390827

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Much work on fuzzy control, covering research, development and applications, has been developed in Europe since the 90's. Nevertheless, the existing books in the field are compilations of articles without interconnection or logical structure or they express the personal point of view of the author. This book compiles the developments of researchers with demonstrated experience in the field of fuzzy control following a logic structure and a unified the style. The first chapters of the book are dedicated to the introduction of the main fuzzy logic techniques, where the following chapters focus on concrete applications. This book is supported by the EUSFLAT and CEA-IFAC societies, which include a large number of researchers in the field of fuzzy logic and control. The central topic of the book, Fuzzy Control, is one of the main research and development lines covered by these associations.