Bio-inspired Optimization of Interval Type-2 Fuzzy Controllers

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 291)

Abstract

A review of the optimization methods used in the design of type-2 fuzzy systems, which are relatively novel models of imprecision, has been considered in this paper. The fundamental focus of the work has been based on the basic reasons of the need for optimizing type-2 fuzzy systems for different areas of application. Recently, bio-inspired methods have emerged as powerful optimization algorithms for solving complex problems. In the case of designing type-2 fuzzy systems for particular applications, the use of bio-inspired optimization methods have helped in the complex task of finding the appropriate parameter values and structure of the fuzzy systems. In this paper, we consider the application of genetic algorithms, particle swarm optimization and ant colony optimization as three different paradigms that help in the design of optimal type-2 fuzzy systems. We also provide a comparison of the different optimization methods for the case of designing type-2 fuzzy systems.

Keywords

Intelligent Control Type-2 Fuzzy Logic Interval Fuzzy Logic 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Division of Graduate StudiesTijuana Institute of TechnologyTijuanaMexico

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