Fuzzy Control and Identification

Fuzzy Control and Identification

Author: John H. Lilly

Publisher: John Wiley & Sons

ISBN: 1118097815

Category: Technology & Engineering

Page: 248

View: 796

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This book gives an introduction to basic fuzzy logic and Mamdaniand Takagi-Sugeno fuzzy systems. The text shows howthese can be used to control complex nonlinear engineering systems,while also also suggesting several approaches to modelingof complex engineering systems with unknown models. Finally, fuzzy modeling and control methods are combined in thebook, to create adaptive fuzzy controllers, ending withan example of an obstacle-avoidance controller for an autonomousvehicle using modus ponendo tollens logic.

Fuzzy Logic, Identification and Predictive Control

Fuzzy Logic, Identification and Predictive Control

Author: Jairo Jose Espinosa Oviedo

Publisher: Springer Science & Business Media

ISBN: 9781846280870

Category: Technology & Engineering

Page: 264

View: 713

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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.

Fuzzy System Identification and Adaptive Control

Fuzzy System Identification and Adaptive Control

Author: Ruiyun Qi

Publisher: Springer

ISBN: 9783030198824

Category: Technology & Engineering

Page: 282

View: 869

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This book provides readers with a systematic and unified framework for identification and adaptive control of Takagi–Sugeno (T–S) fuzzy systems. Its design techniques help readers applying these powerful tools to solve challenging nonlinear control problems. The book embodies a systematic study of fuzzy system identification and control problems, using T–S fuzzy system tools for both function approximation and feedback control of nonlinear systems. Alongside this framework, the book also: introduces basic concepts of fuzzy sets, logic and inference system; discusses important properties of T–S fuzzy systems; develops offline and online identification algorithms for T–S fuzzy systems; investigates the various controller structures and corresponding design conditions for adaptive control of continuous-time T–S fuzzy systems; develops adaptive control algorithms for discrete-time input–output form T–S fuzzy systems with much relaxed design conditions, and discrete-time state-space T–S fuzzy systems; and designs stable parameter-adaptation algorithms for both linearly and nonlinearly parameterized T–S fuzzy systems. The authors address adaptive fault compensation problems for T–S fuzzy systems subject to actuator faults. They cover a broad spectrum of related technical topics and to develop a substantial set of adaptive nonlinear system control tools. Fuzzy System Identification and Adaptive Control helps engineers in the mechanical, electrical and aerospace fields, to solve complex control design problems. The book can be used as a reference for researchers and academics in nonlinear, intelligent, adaptive and fault-tolerant control.

Fuzzy Modeling and Fuzzy Control

Fuzzy Modeling and Fuzzy Control

Author: Huaguang Zhang

Publisher: Springer Science & Business Media

ISBN: 9780817645397

Category: Technology & Engineering

Page: 416

View: 762

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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.

Recent Advances in Electrical Engineering and Control Applications

Recent Advances in Electrical Engineering and Control Applications

Author: Mohammed Chadli

Publisher: Springer

ISBN: 9783319489292

Category: Technology & Engineering

Page: 418

View: 376

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This book of proceedings includes papers presenting the state of art in electrical engineering and control theory as well as their applications. The topics focus on classical as well as modern methods for modeling, control, identification and simulation of complex systems with applications in science and engineering. The papers were selected from the hottest topic areas, such as control and systems engineering, renewable energy, faults diagnosis—faults tolerant control, large-scale systems, fractional order systems, unconventional algorithms in control engineering, signals and communications. The control and design of complex systems dynamics, analysis and modeling of its behavior and structure is vitally important in engineering, economics and in science generally science today. Examples of such systems can be seen in the world around us and are a part of our everyday life. Application of modern methods for control, electronics, signal processing and more can be found in our mobile phones, car engines, home devices like washing machines is as well as in such advanced devices as space probes and systems for communicating with them. All these technologies are part of technological backbone of our civilization, making further research and hi-tech applications essential. The rich variety of contributions appeals to a wide audience, including researchers, students and academics.

System Identification and Adaptive Control

System Identification and Adaptive Control

Author: Yiannis Boutalis

Publisher: Springer Science & Business

ISBN: 9783319063645

Category: Technology & Engineering

Page: 313

View: 304

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Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model stems from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering systems. All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects in: • contemporary power generation; • process control and • conventional benchmarking problems. Researchers and graduate students working in adaptive estimation and intelligent control will find Neurofuzzy Adaptive Control of interest both for the currency of its models and because it demonstrates their relevance for real systems. The monograph also shows industrial engineers how to test intelligent adaptive control easily using proven theoretical results.

Fuzzy Model Identification

Fuzzy Model Identification

Author: Hans Hellendoorn

Publisher: Springer Science & Business Media

ISBN: 9783642607677

Category: Computers

Page: 319

View: 101

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During the past few years two principally different approaches to the design of fuzzy controllers have emerged: heuristics-based design and model-based design. The main motivation for the heuristics-based design is given by the fact that many industrial processes are still controlled in one of the following two ways: - The process is controlled manually by an experienced operator. - The process is controlled by an automatic control system which needs manual, on-line 'trimming' of its parameters by an experienced operator. In both cases it is enough to translate in terms of a set of fuzzy if-then rules the operator's manual control algorithm or manual on-line 'trimming' strategy in order to obtain an equally good, or even better, wholly automatic fuzzy control system. This implies that the design of a fuzzy controller can only be done after a manual control algorithm or trimming strategy exists. It is admitted in the literature on fuzzy control that the heuristics-based approach to the design of fuzzy controllers is very difficult to apply to multiple-inputjmultiple-output control problems which represent the largest part of challenging industrial process control applications. Furthermore, the heuristics-based design lacks systematic and formally verifiable tuning tech niques. Also, studies of the stability, performance, and robustness of a closed loop system incorporating a heuristics-based fuzzy controller can only be done via extensive simulations.

Fuzzy Control Systems Design and Analysis

Fuzzy Control Systems Design and Analysis

Author: Kazuo Tanaka

Publisher: John Wiley & Sons

ISBN: 9780471465225

Category: Science

Page: 320

View: 694

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A comprehensive treatment of model-based fuzzy controlsystems This volume offers full coverage of the systematic framework forthe stability and design of nonlinear fuzzy control systems.Building on the Takagi-Sugeno fuzzy model, authors Tanaka and Wangaddress a number of important issues in fuzzy control systems,including stability analysis, systematic design procedures,incorporation of performance specifications, numericalimplementations, and practical applications. Issues that have not been fully treated in existing texts, suchas stability analysis, systematic design, and performance analysis,are crucial to the validity and applicability of fuzzy controlmethodology. Fuzzy Control Systems Design and Analysis addressesthese issues in the framework of parallel distributed compensation,a controller structure devised in accordance with the fuzzymodel. This balanced treatment features an overview of fuzzy control,modeling, and stability analysis, as well as a section on the useof linear matrix inequalities (LMI) as an approach to fuzzy designand control. It also covers advanced topics in model-based fuzzycontrol systems, including modeling and control of chaotic systems.Later sections offer practical examples in the form of detailedtheoretical and experimental studies of fuzzy control in roboticsystems and a discussion of future directions in the field. Fuzzy Control Systems Design and Analysis offersan advanced treatment of fuzzy control that makes a usefulreference for researchers and a reliable text for advanced graduatestudents in the field.

Algorithms and Architectures for Real-Time Control 1992

Algorithms and Architectures for Real-Time Control 1992

Author: P.J. Fleming

Publisher: Elsevier

ISBN: 9781483297934

Category: Technology & Engineering

Page: 363

View: 215

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This Workshop focuses on such issues as control algorithms which are suitable for real-time use, computer architectures which are suitable for real-time control algorithms, and applications for real-time control issues in the areas of parallel algorithms, multiprocessor systems, neural networks, fault-tolerance systems, real-time robot control identification, real-time filtering algorithms, control algorithms, fuzzy control, adaptive and self-tuning control, and real-time control applications.

Fuzzy Logic for the Applications to Complex Systems

Fuzzy Logic for the Applications to Complex Systems

Author: Weiling Chiang

Publisher: World Scientific

ISBN: 9789814548373

Category:

Page: 592

View: 731

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This volume presents an interesting mix of topics on complex systems such as information systems, engineering systems, fuzzy neural systems, image processing, robotics, fuzzy control, genetic algorithms, and fuzzy decision making. The contributions come from 12 countries, and provide a clear picture of fuzzy logic applications worldwide. Contents:LIFE Project in Japan (T Terano & K Nakamura)Fuzzy Models and Explicit Functions (L T Koczy & P Varlaki)A Precedent-Based Legal Judgement System Using Fuzzy Relationship Database (K Hirota et al.)The Design of an Adaptive Multiple Agent Constraint-Based Controller for a Complex Hydraulic System (P P Wang et al.)Automatic Labeling of Human Brain Structures in 3D MRI Using Fuzzy Logic (J Yen et al.)Auto-Generation of Fuzzy Production Rules Using Hyper-Cone Membership Function by Genetic Algorithm (H Inoue et al.)Weighted Fuzzy Expected Values and Their Applications (A Kandel & M Friedman)Combining Fuzzy Quantifiers (A L Ralescu et al.)Combining Fuzzy Quantifiers (A L Ralescu et al.)Principal Components, B-Splines, and Fuzzy System Reduction (J Yen et al.)Conditioning in Possibility Theory (A Ramer)User Equilibrium in Traffic Assignment — An Application of Variational Inequality with Fuzzy Functions (H-F Wang & H-S Liao)Applicable Conditions on the Linear Interpolative Reasoning Method in Sparse Fuzzy Rule Bases (M Mizumoto & Y Shi)and other papers Readership: Computer scientists and control engineers. keywords:

Modelling, Simulation and Control of Non-linear Dynamical Systems

Modelling, Simulation and Control of Non-linear Dynamical Systems

Author: Patricia Melin

Publisher: CRC Press

ISBN: 9781000611960

Category: Mathematics

Page: 262

View: 712

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These authors use soft computing techniques and fractal theory in this new approach to mathematical modeling, simulation and control of complexion-linear dynamical systems. First, a new fuzzy-fractal approach to automated mathematical modeling of non-linear dynamical systems is presented. It is illustrated with examples on the PROLOG programming la