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Download the fantastic book titled Fuzzy Modeling for Control written by Robert Babuška, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Fuzzy Modeling for Control", which was released on 06 December 2012. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Mathematics genre.

Summary of Fuzzy Modeling for Control by Robert Babuška PDF

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.


Detail About Fuzzy Modeling for Control PDF

  • Author : Robert Babuška
  • Publisher : Springer Science & Business Media
  • Genre : Mathematics
  • Total Pages : 269 pages
  • ISBN : 9401148686
  • PDF File Size : 20,6 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Fuzzy Modeling for Control

Fuzzy Modeling for Control
  • Publisher : Springer
  • File Size : 50,9 Mb
  • Release Date : 26 October 2012
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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,

Fuzzy Modeling and Control

Fuzzy Modeling and Control
  • Publisher : Physica
  • File Size : 33,7 Mb
  • Release Date : 19 March 2013
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In the last ten years, a true explosion of investigations into fuzzy modeling and its applications in control, diagnostics, decision making, optimization, pattern recognition, robotics, etc. has been observed. The

Analytical Methods in Fuzzy Modeling and Control

Analytical Methods in Fuzzy Modeling and Control
  • Publisher : Springer
  • File Size : 55,8 Mb
  • Release Date : 22 January 2009
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This book is focused on mathematical analysis and rigorous design methods for fuzzy control systems based on Takagi-Sugeno fuzzy models, sometimes called Takagi-Sugeno-Kang models.

Fuzzy Modeling and Control

Fuzzy Modeling and Control
  • Publisher : Unknown Publisher
  • File Size : 48,5 Mb
  • Release Date : 05 June 2018
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Fuzzy Modeling and Control: Methods, Applications and Research opens by recommending a new fuzzy RANSAC algorithm based on the reinforcement learning concept to improve modeling performance under the outlier noise.

Fuzzy Modeling for Control

Fuzzy Modeling for Control
  • Publisher : Springer Science & Business Media
  • File Size : 34,7 Mb
  • Release Date : 06 December 2012
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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,

Fuzzy Modeling and Fuzzy Control

Fuzzy Modeling and Fuzzy Control
  • Publisher : Springer Science & Business Media
  • File Size : 21,8 Mb
  • Release Date : 17 October 2007
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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

Essentials of Fuzzy Modeling and Control

Essentials of Fuzzy Modeling and Control
  • Publisher : Unknown Publisher
  • File Size : 27,6 Mb
  • Release Date : 18 June 1994
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This book offers a thorough introduction to the field of fuzzy logic with complete coverage of both relevant theory and applications. With its comprehensive presentation of fuzzy logic as well

Fuzzy Modeling and Control: Theory and Applications

Fuzzy Modeling and Control: Theory and Applications
  • Publisher : Springer
  • File Size : 48,7 Mb
  • Release Date : 14 August 2014
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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

Fuzzy Decision Making in Modeling and Control

Fuzzy Decision Making in Modeling and Control
  • Publisher : World Scientific
  • File Size : 30,8 Mb
  • Release Date : 18 June 2024
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Decision making and control are two fields with distinct methods for solving problems, and yet they are closely related. This book bridges the gap between decision making and control in

Fuzzy Control Systems Design and Analysis

Fuzzy Control Systems Design and Analysis
  • Publisher : John Wiley & Sons
  • File Size : 37,9 Mb
  • Release Date : 07 April 2004
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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