Fuzzy Control and Identification

Fuzzy Control and Identification
Title Fuzzy Control and Identification PDF eBook
Author John H. Lilly
Publisher John Wiley & Sons
Pages 199
Release 2011-03-10
Genre Technology & Engineering
ISBN 1118097815

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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.

Fuzzy Logic, Identification and Predictive Control

Fuzzy Logic, Identification and Predictive Control
Title Fuzzy Logic, Identification and Predictive Control PDF eBook
Author Jairo Jose Espinosa Oviedo
Publisher Springer Science & Business Media
Pages 274
Release 2007-01-04
Genre Technology & Engineering
ISBN 1846280877

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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 Control and Fuzzy Systems

Fuzzy Control and Fuzzy Systems
Title Fuzzy Control and Fuzzy Systems PDF eBook
Author Witold Pedrycz
Publisher *Research Studies Press
Pages 376
Release 1993-08-17
Genre Computers
ISBN

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Examines the methodology and algorithms of fuzzy sets considered mainly in the context of control engineering and system modelling and analysis. Special emphasis is focused on the processing of fuzzy information realized with the aid of fuzzy relational structures and their extensions.

Fuzzy Control

Fuzzy Control
Title Fuzzy Control PDF eBook
Author Kevin M. Passino
Publisher Prentice Hall
Pages 506
Release 1998
Genre Computers
ISBN

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Introduction; Fuzzy control: the basics; Case studies in design and implementation; nonlinear analysis; Fuzzy identification and estimation; Adaptive fuzzy control; Fuzzy supervisory control; Perspectives on fuzzy control.

Fuzzy Model Identification

Fuzzy Model Identification
Title Fuzzy Model Identification PDF eBook
Author Hans Hellendoorn
Publisher Springer
Pages 350
Release 1997
Genre Computers
ISBN

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Introduction; General overview; Fuzzy identification from a grey box modeling point of view; Clustering methods; Constructing fuzzy models by product space clustering; Identification of Takagi-Sugeno fuzzy models via clustering and Hough transform; Rapid prototyping of fuzzy models based on hierarchical clustering; Neural networks; Fuzzy identification using methods of intelligent data analysis; Identification of singleton fuzzy models via fuzzy hyperrectangular composite NN; Genetic algorithms; Identification of linguistic fuzzy models by means of genetic algorithms.; Optimization of fuzzy models by global numeric optimizaton; Artificial intelligence; Identification of linguistic fuzzy models based on learning.

Fuzzy Modeling for Control

Fuzzy Modeling for Control
Title Fuzzy Modeling for Control PDF eBook
Author Robert Babuška
Publisher Springer Science & Business Media
Pages 269
Release 2012-12-06
Genre Mathematics
ISBN 9401148686

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Rule-based fuzzy modeling has been recognised as a powerful technique for the modeling of partly-known nonlinear systems. Fuzzy models can effectively integrate information from different sources, such as physical laws, empirical models, measurements and heuristics. Application areas of fuzzy models include prediction, decision support, system analysis, control design, etc. Fuzzy Modeling for Control addresses fuzzy modeling from the systems and control engineering points of view. It focuses on the selection of appropriate model structures, on the acquisition of dynamic fuzzy models from process measurements (fuzzy identification), and on the design of nonlinear controllers based on fuzzy models. To automatically generate fuzzy models from measurements, a comprehensive methodology is developed which employs fuzzy clustering techniques to partition the available data into subsets characterized by locally linear behaviour. The relationships between the presented identification method and linear regression are exploited, allowing for the combination of fuzzy logic techniques with standard system identification tools. Attention is paid to the trade-off between the accuracy and transparency of the obtained fuzzy models. Control design based on a fuzzy model of a nonlinear dynamic process is addressed, using the concepts of model-based predictive control and internal model control with an inverted fuzzy model. To this end, methods to exactly invert specific types of fuzzy models are presented. In the context of predictive control, branch-and-bound optimization is applied. The main features of the presented techniques are illustrated by means of simple examples. In addition, three real-world applications are described. Finally, software tools for building fuzzy models from measurements are available from the author.

Fuzzy System Identification and Adaptive Control

Fuzzy System Identification and Adaptive Control
Title Fuzzy System Identification and Adaptive Control PDF eBook
Author Ruiyun Qi
Publisher Springer
Pages 0
Release 2020-06-10
Genre Technology & Engineering
ISBN 9783030198848

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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.