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Book Advanced Takagi   Sugeno Fuzzy Systems

Download or read book Advanced Takagi Sugeno Fuzzy Systems written by Abdellah Benzaouia and published by Springer. This book was released on 2014-06-07 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph puts the reader in touch with a decade’s worth of new developments in the field of fuzzy control specifically those of the popular Takagi-Sugeno (T-S) type. New techniques for stabilizing control analysis and design based on multiple Lyapunov functions and linear matrix inequalities (LMIs), are proposed. All the results are illustrated with numerical examples and figures and a rich bibliography is provided for further investigation. Control saturations are taken into account within the fuzzy model. The concept of positive invariance is used to obtain sufficient asymptotic stability conditions for the fuzzy system with constrained control inside a subset of the state space. The authors also consider the non-negativity of the states. This is of practical importance in many chemical, physical and biological processes that involve quantities that have intrinsically constant and non-negative sign: concentration of substances, level of liquids, etc. Results for linear systems are then extended to linear systems with delay. It is shown that LMI techniques can usually handle the new constraint of non-negativity of the states when care is taken to use an adequate Lyapunov function. From these foundations, the following further problems are also treated: · asymptotic stabilization of uncertain T-S fuzzy systems with time-varying delay, focusing on delay-dependent stabilization synthesis based on parallel distributed controller (PDC); · asymptotic stabilization of uncertain T-S fuzzy systems with multiple delays, focusing on delay-dependent stabilization synthesis based on PDC with results obtained under linear programming; · design of delay-independent, observer-based, H-infinity control for T–S fuzzy systems with time varying delay; and · asymptotic stabilization of 2-D T–S fuzzy systems. Advanced Takagi–Sugeno Fuzzy Systems provides researchers and graduate students interested in fuzzy control systems with further approaches based LMI and LP.

Book Advanced Takagi Sugeno Fuzzy Systems

Download or read book Advanced Takagi Sugeno Fuzzy Systems written by Abdellah Benzaouia and published by . This book was released on 2014-06-30 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Fuzzy Control and Identification

Download or read book Fuzzy Control and Identification written by John H. Lilly and published by John Wiley & Sons. This book was released on 2011-03-10 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives an introduction to basic fuzzy logic and Mamdani and Takagi-Sugeno fuzzy systems. The text shows how these can be used to control complex nonlinear engineering systems, while also also suggesting several approaches to modeling of complex engineering systems with unknown models. Finally, fuzzy modeling and control methods are combined in the book, to create adaptive fuzzy controllers, ending with an example of an obstacle-avoidance controller for an autonomous vehicle using modus ponendo tollens logic.

Book Fuzzy Control Systems Design and Analysis

Download or read book Fuzzy Control Systems Design and Analysis written by Kazuo Tanaka and published by John Wiley & Sons. This book was released on 2004-04-07 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive treatment of model-based fuzzy control systems This volume offers full coverage of the systematic framework for the stability and design of nonlinear fuzzy control systems. Building on the Takagi-Sugeno fuzzy model, authors Tanaka and Wang address a number of important issues in fuzzy control systems, including stability analysis, systematic design procedures, incorporation of performance specifications, numerical implementations, and practical applications. Issues that have not been fully treated in existing texts, such as stability analysis, systematic design, and performance analysis, are crucial to the validity and applicability of fuzzy control methodology. Fuzzy Control Systems Design and Analysis addresses these issues in the framework of parallel distributed compensation, a controller structure devised in accordance with the fuzzy model. This balanced treatment features an overview of fuzzy control, modeling, and stability analysis, as well as a section on the use of linear matrix inequalities (LMI) as an approach to fuzzy design and control. It also covers advanced topics in model-based fuzzy control systems, including modeling and control of chaotic systems. Later sections offer practical examples in the form of detailed theoretical and experimental studies of fuzzy control in robotic systems and a discussion of future directions in the field. Fuzzy Control Systems Design and Analysis offers an advanced treatment of fuzzy control that makes a useful reference for researchers and a reliable text for advanced graduate students in the field.

Book LMI Approach to Analysis and Control of Takagi Sugeno Fuzzy Systems with Time Delay

Download or read book LMI Approach to Analysis and Control of Takagi Sugeno Fuzzy Systems with Time Delay written by Chong Lin and published by Springer Science & Business Media. This book was released on 2007-02-08 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the latest developments in the analysis and control of nonlinear time-delay systems using T-S fuzzy model approach. It presents a comprehensive, up-to-date, and detailed treatment of many interesting topics, such as stability analysis, stabilization, fuzzy variable structure control, fuzzy tracking control, fuzzy observer design, and filter design for T-S fuzzy systems with time delay.

Book Evolving Fuzzy Systems   Methodologies  Advanced Concepts and Applications

Download or read book Evolving Fuzzy Systems Methodologies Advanced Concepts and Applications written by Edwin Lughofer and published by Springer Science & Business Media. This book was released on 2011-01-19 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today’s real-world applications, there is an increasing demand of integrating new information and knowledge on-demand into model building processes to account for changing system dynamics, new operating conditions, varying human behaviors or environmental influences. Evolving fuzzy systems (EFS) are a powerful tool to cope with this requirement, as they are able to automatically adapt parameters, expand their structure and extend their memory on-the-fly, allowing on-line/real-time modeling. This book comprises several evolving fuzzy systems approaches which have emerged during the last decade and highlights the most important incremental learning methods used. The second part is dedicated to advanced concepts for increasing performance, robustness, process-safety and reliability, for enhancing user-friendliness and enlarging the field of applicability of EFS and for improving the interpretability and understandability of the evolved models. The third part underlines the usefulness and necessity of evolving fuzzy systems in several online real-world application scenarios, provides an outline of potential future applications and raises open problems and new challenges for the next generation evolving systems, including human-inspired evolving machines. The book includes basic principles, concepts, algorithms and theoretic results underlined by illustrations. It is dedicated to researchers from the field of fuzzy systems, machine learning, data mining and system identification as well as engineers and technicians who apply data-driven modeling techniques in real-world systems.

Book Evolving Intelligent Systems

Download or read book Evolving Intelligent Systems written by Plamen Angelov and published by John Wiley & Sons. This book was released on 2010-03-25 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: From theory to techniques, the first all-in-one resource for EIS There is a clear demand in advanced process industries, defense, and Internet and communication (VoIP) applications for intelligent yet adaptive/evolving systems. Evolving Intelligent Systems is the first self- contained volume that covers this newly established concept in its entirety, from a systematic methodology to case studies to industrial applications. Featuring chapters written by leading world experts, it addresses the progress, trends, and major achievements in this emerging research field, with a strong emphasis on the balance between novel theoretical results and solutions and practical real-life applications. Explains the following fundamental approaches for developing evolving intelligent systems (EIS): the Hierarchical Prioritized Structure the Participatory Learning Paradigm the Evolving Takagi-Sugeno fuzzy systems (eTS+) the evolving clustering algorithm that stems from the well-known Gustafson-Kessel offline clustering algorithm Emphasizes the importance and increased interest in online processing of data streams Outlines the general strategy of using the fuzzy dynamic clustering as a foundation for evolvable information granulation Presents a methodology for developing robust and interpretable evolving fuzzy rule-based systems Introduces an integrated approach to incremental (real-time) feature extraction and classification Proposes a study on the stability of evolving neuro-fuzzy recurrent networks Details methodologies for evolving clustering and classification Reveals different applications of EIS to address real problems in areas of: evolving inferential sensors in chemical and petrochemical industry learning and recognition in robotics Features downloadable software resources Evolving Intelligent Systems is the one-stop reference guide for both theoretical and practical issues for computer scientists, engineers, researchers, applied mathematicians, machine learning and data mining experts, graduate students, and professionals.

Book Control and Filtering of Fuzzy Systems with Switched Parameters

Download or read book Control and Filtering of Fuzzy Systems with Switched Parameters written by Shanling Dong and published by Springer Nature. This book was released on 2019-11-25 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Takagi Sugeno Fuzzy Systems Non fragile H infinity Filtering

Download or read book Takagi Sugeno Fuzzy Systems Non fragile H infinity Filtering written by Xiao-Heng Chang and published by Springer. This book was released on 2012-04-23 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: Takagi-Sugeno Fuzzy Systems Non-fragile H-infinity Filtering investigates the problem of non-fragile H-infinity filter design for Takagi-Sugeno (T-S) fuzzy systems. Given a T-S fuzzy system, the objective of this book is to design an H-infinity filter with the gain variations such that the filtering error system guarantees a prescribed H-infinity performance level. Furthermore, it demonstrates that the solution of non-fragile H-infinity filter design problem can be obtained by solving a set of linear matrix inequalities (LMIs). The intended audiences are graduate students and researchers both from the fields of engineering and mathematics. Dr. Xiao-Heng Chang is an Associate Professor at the College of Engineering, Bohai University, Jinzhou, Liaoning, China.

Book Multiple Fuzzy Classification Systems

Download or read book Multiple Fuzzy Classification Systems written by Rafał Scherer and published by Springer. This book was released on 2012-06-26 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy classifiers are important tools in exploratory data analysis, which is a vital set of methods used in various engineering, scientific and business applications. Fuzzy classifiers use fuzzy rules and do not require assumptions common to statistical classification. Rough set theory is useful when data sets are incomplete. It defines a formal approximation of crisp sets by providing the lower and the upper approximation of the original set. Systems based on rough sets have natural ability to work on such data and incomplete vectors do not have to be preprocessed before classification. To achieve better performance than existing machine learning systems, fuzzy classifiers and rough sets can be combined in ensembles. Such ensembles consist of a finite set of learning models, usually weak learners. The present book discusses the three aforementioned fields – fuzzy systems, rough sets and ensemble techniques. As the trained ensemble should represent a single hypothesis, a lot of attention is placed on the possibility to combine fuzzy rules from fuzzy systems being members of classification ensemble. Furthermore, an emphasis is placed on ensembles that can work on incomplete data, thanks to rough set theory. .

Book Fuzzy Logic  Identification and Predictive Control

Download or read book Fuzzy Logic Identification and Predictive Control written by Jairo Jose Espinosa Oviedo and published by Springer Science & Business Media. This book was released on 2007-01-04 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern industrial processes and systems require adaptable advanced control protocols able to deal with circumstances demanding "judgement” rather than simple "yes/no”, "on/off” responses: circumstances where a linguistic description is often more relevant than a cut-and-dried numerical one. The ability of fuzzy systems to handle numeric and linguistic information within a single framework renders them efficacious for this purpose. Fuzzy Logic, Identification and Predictive Control first shows you how to construct static and dynamic fuzzy models using the numerical data from a variety of real industrial systems and simulations. The second part exploits such models to design control systems employing techniques like data mining. This monograph presents a combination of fuzzy control theory and industrial serviceability that will make a telling contribution to your research whether in the academic or industrial sphere and also serves as a fine roundup of the fuzzy control area for the graduate student.

Book Stabilization of Takagi Sugeno Fuzzy Systems with Application on Greenhouse

Download or read book Stabilization of Takagi Sugeno Fuzzy Systems with Application on Greenhouse written by Meriem Nachidi and published by . This book was released on 2009 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Analysis and Synthesis of Fuzzy Control Systems

Download or read book Analysis and Synthesis of Fuzzy Control Systems written by Gang Feng and published by CRC Press. This book was released on 2018-09-03 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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®.

Book Advanced Intelligent Computing

Download or read book Advanced Intelligent Computing written by De-Shuang Huang and published by Springer. This book was released on 2012-02-10 with total page 728 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 7th International Conference on Intelligent Computing, ICIC 2011, held in Zhengzhou, China, in August 2011. The 94 revised full papers presented were carefully reviewed and selected from 832 submissions. The papers are organized in topical sections on neural networks; machine learning theory and methods; fuzzy theory and models; fuzzy systems and soft computing; evolutionary learning & genetic algorithms; swarm intelligence and optimization; intelligent computing in computer vision; intelligent computing in image processing; biometrics with applications to individual security/forensic sciences; intelligent image/document retrievals; natural language processing and computational linguistics; intelligent data fusion and information security; intelligent computing in pattern recognition; intelligent agent and web applications; intelligent computing in scheduling; intelligent control and automation.

Book Handbook of Research on Advanced Intelligent Control Engineering and Automation

Download or read book Handbook of Research on Advanced Intelligent Control Engineering and Automation written by Azar, Ahmad Taher and published by IGI Global. This book was released on 2014-11-30 with total page 795 pages. Available in PDF, EPUB and Kindle. Book excerpt: In industrial engineering and manufacturing, control of individual processes and systems is crucial to developing a quality final product. Rapid developments in technology are pioneering new techniques of research in control and automation with multi-disciplinary applications in electrical, electronic, chemical, mechanical, aerospace, and instrumentation engineering. The Handbook of Research on Advanced Intelligent Control Engineering and Automation presents the latest research into intelligent control technologies with the goal of advancing knowledge and applications in various domains. This text will serve as a reference book for scientists, engineers, and researchers, as it features many applications of new computational and mathematical tools for solving complicated problems of mathematical modeling, simulation, and control.

Book Analysis and Synthesis of Takagi Sugeno Fuzzy Systems

Download or read book Analysis and Synthesis of Takagi Sugeno Fuzzy Systems written by Petr Hušek and published by . This book was released on 2011 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: