한국지능시스템학회:학술대회논문집 (Proceedings of the Korean Institute of Intelligent Systems Conference)
- 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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- Pages.354-360
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- 1998
Co-evolutionary Genetic Algorithm for Designing and Optimaizing Fuzzy Controller
- Byung, Jun-Hyo (Robotics and Intelligent Information System Laboratory Schoole of electrical and Electronic Engineering, Chung-Ang University) ;
- Bo, Sim-Kwee (Robotics and Intelligent Information System Laboratory Schoole of electrical and Electronic Engineering, Chung-Ang University)
- 발행 : 1998.10.01
초록
In general, it is very difficult to find optimal fuzzy rules by experience when a system is dynamical and/or complex. Futhermore proper fuzzy partitioning is not deterministic and there is no unique solution. Therefore we propose a new design method of an optimal fuzzy logic controller, that is a co-evolutionary genetic algorithm finding optimal fuzzy rule and proper membership functions at the same time. We formalize the relation between fuzzy rules and membership functions in terms of fitness. We review the typical approaching methods to co-evolutionary genetic algorithms , and then classify them by fitness relation matrix. Applications of the proposed method to a path planning problem of autonomous mobile robots when moving objects exist are presented to demonstrate the performance and effectiveness of the method.
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