Advances in Industrial Control

Espinosa Oviedo, Jairo Jose; Vandewalle, Joos P.L.; Wertz, Vincent

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.

Details

Published by: Springer

Publication Date: 2004-12-03

Format: Hardcover

ISBN-13: 9781852338282

DOI: 10.1007/b138626

Dimensions: 235cm x155cm

Pages: 264