The Korea Institute of Information and Commucation Engineering 2008; 6(2): 222-227
Published online June 30, 2008
© Korea Institute of Information and Communication Engineering
Optimization of Fuzzy Car Controller Using Genetic Algorithm
The important problem in designing a Fuzzy Logic Controller(FLC) is generation of fuzzy control rules and it is usually the case that they are given by human experts of the problem domain. However, it is difficult to find an well-trained expert to any given problem. In this paper, I describes an application of genetic algorithm, a well-known global search algorithm to automatic generation of fuzzy control rules for FLC design. Fuzzy rules are automatically generated by evolving initially given fuzzy rules and membership functions associated fuzzy linguistic terms. Using genetic algorithm efficient fuzzy rules can be generated without any prior knowledge about the domain problem. In addition expert knowledge can be easily incorporated into rule generation for performance enhancement. We experimented genetic algorithm with a non-trivial vehicle controling problem. Our experimental results showed that genetic algorithm is efficient for designing any complex control system and the resulting system is robust.
Keywords Genetic algorithm,Fuzzy car controller,Optimization
PDF
Standard view
Export citation
Share Article
The Korea Institute of Information and Commucation Engineering 2008; 6(2): 222-227
Published online June 30, 2008
Copyright © Korea Institute of Information and Communication Engineering.
Optimization of Fuzzy Car Controller Using Genetic Algorithm
Kim, Bong-Gi;Song, Jin-Kook;Shin, Chang-Doon;
Division of Computer Science & Engineering, Jinju National University, Division of Computer Science & Engineering, Jinju National University, Department of Visual Contents, Hallym College
Abstract
The important problem in designing a Fuzzy Logic Controller(FLC) is generation of fuzzy control rules and it is usually the case that they are given by human experts of the problem domain. However, it is difficult to find an well-trained expert to any given problem. In this paper, I describes an application of genetic algorithm, a well-known global search algorithm to automatic generation of fuzzy control rules for FLC design. Fuzzy rules are automatically generated by evolving initially given fuzzy rules and membership functions associated fuzzy linguistic terms. Using genetic algorithm efficient fuzzy rules can be generated without any prior knowledge about the domain problem. In addition expert knowledge can be easily incorporated into rule generation for performance enhancement. We experimented genetic algorithm with a non-trivial vehicle controling problem. Our experimental results showed that genetic algorithm is efficient for designing any complex control system and the resulting system is robust.
Keywords: Genetic algorithm,Fuzzy car controller,Optimization
