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Fuzzy Logic, Identification and Predictive Control

The complexity and sensitivity of modern industrial processes and systems increasingly require adaptable advanced control protocols. These controllers have to be able to deal with circumstances demanding "judgement" rather than simple "yes/no", "on/off" responses, circu...

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Bibliographic Details
Main Authors: Espinosa Oviedo, Jairo Jose. (Author, http://id.loc.gov/vocabulary/relators/aut), Vandewalle, Joos P.L. (http://id.loc.gov/vocabulary/relators/aut), Wertz, Vincent. (http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: London : Springer London : Imprint: Springer, 2005.
Edition:1st ed. 2005.
Series:Advances in Industrial Control,
Subjects:
Electrical engineering.
Information storage and retrieval.
Artificial intelligence.
Control engineering.
Computational complexity.
Electrical Engineering.
Information Storage and Retrieval.
Artificial Intelligence.
Control and Systems Theory.
Complexity.
Online Access:https://doi.org/10.1007/b138626
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Table of Contents:
  • Fuzzy Modeling
  • Fuzzy Modeling
  • Constructing Fuzzy Models from Input-Output Data
  • Fuzzy Modeling with Linguistic Integrity: A Tool for Data Mining
  • Nonlinear Identification Using Fuzzy Models
  • Fuzzy Control
  • Fuzzy Control
  • Predictive Control Based on Fuzzy Models
  • Robust Nonlinear Predictive Control Using Fuzzy Models
  • Conclusions and Future Perspectives.

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