Co-Evolution of Fuzzy Controller for the Mobile Robot Control | Zendy

Kwang-Sub Byun | Zendy; Chang-Hyun Park | Zendy; Kwee-Bo Sim | Zendy

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Co-Evolution of Fuzzy Controller for the Mobile Robot Control

Author(s) -

Kwang-Sub Byun,

Chang-Hyun Park,

Kwee-Bo Sim

Publication year - 2004

Publication title -

journal of advanced computational intelligence and intelligent informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.172

H-Index - 20

eISSN - 1343-0130

pISSN - 1883-8014

DOI - 10.20965/jaciii.2004.p0356

Subject(s) - defuzzification , computer science , fuzzy logic , fuzzy set operations , fuzzy classification , fuzzy number , fuzzy rule , membership function , adaptive neuro fuzzy inference system , fuzzy control system , mathematical optimization , mobile robot , controller (irrigation) , artificial intelligence , data mining , fuzzy set , mathematics , robot , agronomy , biology

In this paper, we design the fuzzy rules using a modified Nash Genetic Algorithm. Fuzzy rules consist of antecedents and consequents. Because this paper uses the simplified method of Sugeno for the fuzzy inference engine, consequents have not membership functions but constants. Therefore, each fuzzy rule in this paper consists of a membership function in the antecedent and a constant value in the consequent. The main problem in fuzzy systems is how to design the fuzzy rule base. Modified Nash GA coevolves membership functions and parameters in consequents of fuzzy rules. We demonstrate this co-evolutionary algorithm and apply to the design of the fuzzy controller for a mobile robot. From the result of simulation, we compare modified Nash GA with the other co-evolution algorithms and verify the efficacy of this algorithm.

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