Fuzzy Control and Filter Design for Uncertain Fuzzy 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.

Control and Filtering of Fuzzy Systems Under Communication Channels
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.

Uncertain Rule-Based Fuzzy Systems
Uncertain Rule-Based Fuzzy Systems

Author: Jerry M. Mendel

Publisher: Springer

Published: 2017-05-17

Total Pages: 701

ISBN-13: 3319513702

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The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that can model uncertainty — i.e., “type-2” fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications from time-series forecasting to knowledge mining to control. In this new edition, a bottom-up approach is presented that begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty. The author covers fuzzy rule-based systems – from type-1 to interval type-2 to general type-2 – in one volume. For hands-on experience, the book provides information on accessing MatLab and Java software to complement the content. The book features a full suite of classroom material.

Fuzzy Systems
Fuzzy Systems

Author: Ahmad Taher Azar

Publisher: BoD – Books on Demand

Published: 2010-02-01

Total Pages: 230

ISBN-13: 9537619923

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While several books are available today that address the mathematical and philosophical foundations of fuzzy logic, none, unfortunately, provides the practicing knowledge engineer, system analyst, and project manager with specific, practical information about fuzzy system modeling. Those few books that include applications and case studies concentrate almost exclusively on engineering problems: pendulum balancing, truck backeruppers, cement kilns, antilock braking systems, image pattern recognition, and digital signal processing. Yet the application of fuzzy logic to engineering problems represents only a fraction of its real potential. As a method of encoding and using human knowledge in a form that is very close to the way experts think about difficult, complex problems, fuzzy systems provide the facilities necessary to break through the computational bottlenecks associated with traditional decision support and expert systems. Additionally, fuzzy systems provide a rich and robust method of building systems that include multiple conflicting, cooperating, and collaborating experts (a capability that generally eludes not only symbolic expert system users but analysts who have turned to such related technologies as neural networks and genetic algorithms). Yet the application of fuzzy logic in the areas of decision support, medical systems, database analysis and mining has been largely ignored by both the commercial vendors of decision support products and the knowledge engineers who use them.

Model Abstraction in Dynamical Systems: Application to Mobile Robot Control
Model Abstraction in Dynamical Systems: Application to Mobile Robot Control

Author: Patricia Mellodge

Publisher: Springer

Published: 2008-09-18

Total Pages: 126

ISBN-13: 3540707999

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The subject of this book is model abstraction of dynamical systems. The p- mary goal of the work embodied in this book is to design a controller for the mobile robotic car using abstraction. Abstraction provides a means to rep- sent the dynamics of a system using a simpler model while retaining important characteristics of the original system. A second goal of this work is to study the propagation of uncertain initial conditions in the framework of abstraction. The summation of this work is presented in this book. It includes the following: • An overview of the history and current research in mobile robotic control design. • A mathematical review that provides the tools used in this research area. • The development of the robotic car model and both controllers used in the new control design. • A review of abstraction and an extension of these ideas into new system relationship characterizations called traceability and -traceability. • A framework for designing controllers based on abstraction. • An open-loop control design with simulation results. • An investigation of system abstraction with uncertain initial conditions.

Robust Synchronization of Chaotic Systems via Feedback
Robust Synchronization of Chaotic Systems via Feedback

Author: Ricardo Femat

Publisher: Springer

Published: 2009-01-23

Total Pages: 205

ISBN-13: 3540693076

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This pages include the results derived during last ten years about both suppression and synchronization of chaotic -continuous time- systems. Along this time, our concept was to study how the intrinsic properties of dynamical systems can be exploited to suppress and to synchronize the chaotic behavior and what synchronization phen- ena can be found under feedback interconnection. Our findings have caused surprise to us and have stimulated our astonishing capability. Perhaps, reader can imagine our faces with opens eyes like children seeing around objects; which are possibly obvious for others and novel for us. A compilation of our surprises about these findings is being described along this book. Book contains both objectives to share our ama- ment and to show our perspective on synchronization of chaotic systems. Thus, while we were writing the preface, we discussed its scope. Thinking as a book readers, we found that a preface should answer, in few words, the following question: What can the reader find in this book?, reader can find our steps toward understanding of c- otic behavior and the possibility of suppressing and synchronizing it. We firstly show the chaos suppression form experimental domain to potential implementation in high tech system as a levitation system based on High Temperature Superconductors (HTS). This chapter is used as departing point towards a more complicated problem the chaotic synchronization. Then, reader travels by the synchronization of the chaotic behavior world throughout distinct feedback approaches.

Approximate and Noisy Realization of Discrete-Time Dynamical Systems
Approximate and Noisy Realization of Discrete-Time Dynamical Systems

Author: Yasumichi Hasegawa

Publisher: Springer

Published: 2008-06-11

Total Pages: 249

ISBN-13: 3540794344

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This monograph deals with approximation and noise cancellation of dynamical systems which include linear and nonlinear input/output relations. It will be of special interest to researchers, engineers and graduate students who have specialized in ?ltering theory and system theory. From noisy or noiseless data, reductionwillbemade.Anewmethodwhichreducesnoiseormodelsinformation will be proposed. Using this method will allow model description to be treated as noise reduction or model reduction. As proof of the e?cacy, this monograph provides new results and their extensions which can also be applied to nonlinear dynamical systems. To present the e?ectiveness of our method, many actual examples of noise and model information reduction will also be provided. Using the analysis of state space approach, the model reduction problem may have become a major theme of technology after 1966 for emphasizing e?ciency in the ?elds of control, economy, numerical analysis, and others. Noise reduction problems in the analysis of noisy dynamical systems may havebecomeamajorthemeoftechnologyafter1974foremphasizinge?ciencyin control.However,thesubjectsoftheseresearcheshavebeenmainlyconcentrated in linear systems. In common model reduction of linear systems in use today, a singular value decompositionofaHankelmatrixisusedto?ndareducedordermodel.However, the existence of the conditions of the reduced order model are derived without evaluationoftheresultantmodel.Inthecommontypicalnoisereductionoflinear systems in use today, the order and parameters of the systems are determined by minimizing information criterion. Approximate and noisy realization problems for input/output relations can be roughly stated as follows: A. The approximate realization problem. For any input/output map, ?nd one mathematical model such that it is similar totheinput/outputmapandhasalowerdimensionthanthegivenminimalstate spaceofadynamicalsystemwhichhasthesamebehaviortotheinput/outputmap. B. The noisy realization problem.

Fuzzy Control, Estimation and Diagnosis
Fuzzy Control, Estimation and Diagnosis

Author: Magdi S. Mahmoud

Publisher: Springer

Published: 2017-06-15

Total Pages: 704

ISBN-13: 3319549545

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This textbook explains the principles of fuzzy systems in some depth together with information useful in realizing them within computational processes. The various algorithms and example problem solutions are a well-balanced and pertinent aid for research projects, laboratory work and graduate study. In addition to its worked examples, the book also uses end-of-chapter exercises as an instructional aid. The content of the book is developed and extended from material taught for four years in the author’s classes. The text provides a broad overview of fuzzy control, estimation and fault diagnosis. It ranges over various classes of target system and modes of control and then turns to filtering, stabilization, and fault detection and diagnosis. Applications, simulation tools and an appendix on algebraic inequalities complete a unified approach to the analysis of single and interconnected fuzzy systems. Fuzzy Control, Estimation and Fault Detection is a guide for final-year undergraduate and graduate students of electrical and mechanical engineering, computer science and information technology, and will also be instructive for professionals in the information technology sector.

Recent Advances in Learning and Control
Recent Advances in Learning and Control

Author: Vincent D. Blondel

Publisher: Springer Science & Business Media

Published: 2008-01-11

Total Pages: 283

ISBN-13: 1848001541

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This volume is composed of invited papers on learning and control. The contents form the proceedings of a workshop held in January 2008, in Hyderabad that honored the 60th birthday of Doctor Mathukumalli Vidyasagar. The 14 papers, written by international specialists in the field, cover a variety of interests within the broader field of learning and control. The diversity of the research provides a comprehensive overview of a field of great interest to control and system theorists.

Control Systems Theory and Applications for Linear Repetitive Processes
Control Systems Theory and Applications for Linear Repetitive Processes

Author: Eric Rogers

Publisher: Springer Science & Business Media

Published: 2007-07-11

Total Pages: 477

ISBN-13: 3540715371

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After motivating examples, this monograph gives substantial new results on the analysis and control of linear repetitive processes. These include further applications of the abstract model based stability theory which, in particular, shows the critical importance to the dynamics developed of the structure of the initial conditions at the start of each new pass, the development of stability tests and performance bounds in terms of so-called 1D and 2D Lyapunov equations. It presents the development of a major bank of results on the structure and design of control laws, including the case when there is uncertainty in the process model description, together with numerically reliable computational algorithms. Finally, the application of some of these results in the area of iterative learning control is treated --- including experimental results from a chain conveyor system and a gantry robot system.