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Author Espinosa, Jairo.
Title Fuzzy logic, identification, and predictive control / Jairo Espinosa, Joos Vandewalle, Vincent Wertz.
Imprint London ; New York : Springer, 2004.

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Author Espinosa, Jairo.
Series Advances in industrial control, 1430-9491
Advances in industrial control. 1430-9491
Subject Predictive control.
Fuzzy systems.
Alt Name Vandewalle, J. (Joos), 1948-
Wertz, Vincent.
Description 1 online resource (xix, 263 pages) : illustrations.
Bibliography Note Includes bibliographical references (pages 255-259) and index.
Summary "Fuzzy Logic, Identification and Predictive Control is a comprehensive introduction to the use of fuzzy methods in many different control paradigms encompassing robust, model-based, PID-like and predictive control. This combination of fuzzy control theory and industrial serviceability 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."--Jacket.
Contents Cover -- Preface -- Table of Contents -- Part I Fuzzy Modeling -- 1 Fuzzy Modeling. -- 1.1 Function Approximation . -- 1.2 Approximation Capabilities of Takagi ... Sugeno Fuzzy Models -- 1.3 Conclusion and Summary -- 2 Constructing Fuzzy Models from Input-Output Data -- 2.1 Mosaic or Table Lookup Scheme. -- 2.2 Using Gradient Descent -- 2.3 Using Clustering and Gradient Descent -- 2.4 Using Evolutionary Strategies -- 2.5 Generalization and Consequences Estimation. -- 2.6 Example of an Industrial Application -- 2.7 Conclusions -- 3 Fuzzy Modeling with Linguistic Integrity: A Tool for Data Mining -- 3.1 Introduction -- 3.2 Structure of the Fuzzy Model -- 3.3 The AFRELI Algorithm. -- 3.4 The FuZion Algorithm -- 3.5 Examples. -- 3.6 Complexity of the AFRELI Algorithm -- 3.7 Conclusions -- 4 Nonlinear Identification Using Fuzzy Models -- 4.1 System Identification -- 4.2 Basic Structure of the Fuzzy System -- 4.3 Experiment Design for System Identification -- 4.4 Choosing the Regressors -- 4.5 Choosing the Structure. -- 4.6 Calculating the Parameters -- 4.7 Validation -- 4.8 Example: Identification of the Box and Jenkins Gas Furnace Data Set -- 4.9 Identification of Takagi ... Sugeno Fuzzy Models Using Local Linear Identification -- 4.10 Conclusions -- Part II Fuzzy Control -- 5 Fuzzy Control -- 5.1 Model-Free Fuzzy Control -- 5.2 Model Based Fuzzy Control -- 5.3 Conclusions and Future Perspectives -- 6 Predictive Control Based on Fuzzy Models -- 6.1 The Predictive Control Strategy -- 6.2 Unconstrained Nonlinear Predictive Control -- 6.3 Constrained Nonlinear Predictive Control -- 6.4 Conclusions -- 7 Robust Nonlinear Predictive Control Using Fuzzy Models -- 7.1 Introduction -- 7.2 Robust Quadratic Programming -- 7.3 Problem Description -- 7.4 Nominal Solution -- 7.5 Formulation of the MPC Problem as a Robust QP. -- 7.6 The Control Algorithm. -- 7.7 Uncertainty Description in Fuzzy Models -- 7.8 Conclusions and Perspectives -- 8 Conclusions and Future Perspectives -- 8.1 Conclusions and Summary -- 8.2 Perspectives and Future Work. -- Part III Appendices -- A Fuzzy Set Theory -- B Clustering Methods -- C Gradients Used in Identification with Fuzzy Models -- D Discrete Linear Dynamical System Approximation Theorem. -- E Fuzzy Control for a Continuously Variable Transmission -- References.
Note Print version record.
ISBN 1852338288 (alk. paper)
9781852338282 (alk. paper)
1846280877 (electronic bk.)
9781846280870 (electronic bk.)
6610312214
9786610312214
OCLC # 62776356
Additional Format Print version: Espinosa, Jairo. Fuzzy logic, identification, and predictive control. London ; New York : Springer, 2004 1852338288 (DLC) 2004046864 (OCoLC)55104841



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