Design of Self-Tuning Fuzzy Logic Controllers using Genetic Algorithms

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  • Suh, Jae-Kun (Department of Electrical Engineering, Kon-Kuk University) ;
  • Kim, Tae-Eun (Department of Electrical Engineering, Kon-Kuk University) ;
  • Kwon, Hyuk-Jin (Department of Electrical Engineering, Kon-Kuk University) ;
  • Kim, Lark-Kyo (Department of Electrical Engineering, Kon-Kuk University) ;
  • Nam, Moon-Hyon (Department of Electrical Engineering, Kon-Kuk University)
  • Published : 1996.07.22

Abstract

In this paper We proposed a new method to generate fuzzy logic controllers through genetic algorithm(GA). In designing of fuzzy logic controllers encounters difficulties in the selection of optimized member-ship functions, gains and rule base, which is conventionally achieved by a tedious trial-and-error process. This paper develops genetic algorithms for automatic design of high performance fuzzy logic controllers which can overcome nonlinearities in many engineering control applications. The rule-base is coded in base-7 strings by generated from random function. Which can be presented in discrete fuzzy linguistic value, and using membership function with Gaussian curve. To verify the validity of this fuzzy logic controller it is compared with conventional fuzzy logic controller(FLC) and PID controller.

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