標題: Genetic reinforcement learning through symbiotic evolution for fuzzy controller design
作者: Juang, CF
Lin, JY
Lin, CT
電控工程研究所
Institute of Electrical and Control Engineering
關鍵字: genetic reinforcement;fitness value;fuzzy partition;symbiotic evolution;TSK-type fuzzy rules
公開日期: 1-Apr-2000
摘要: An efficient genetic reinforcement learning algorithm for designing fuzzy controllers is proposed in this paper. The genetic algorithm (GA) adopted in this paper is based upon symbiotic evolution which, when applied to fuzzy controller design, complements the local mapping property of a fuzzy rule. Using this Symbiotic-Evolution-based Fuzzy Controller (SEFC) design method, the number of control trials, as well as consumed CPU time, are considerably reduced when compared to traditional GA-based fuzzy controller design methods and other types of genetic reinforcement learning schemes. Moreover, unlike traditional fuzzy controllers, which partition the input space into a grid, SEFC partitions the input space in a flexible way, thus creating fewer fuzzy rules. In SEFC, different types of fuzzy rules whose consequent parts are singletons, fuzzy sets, or linear equations (TSK-type fuzzy rules) are allowed. Further, the free parameters (e.g., centers and widths of membership functions) and fuzzy rules are all tuned automatically. For the TSK-type fuzzy rule especially, which put the proposed learning algorithm in use, only the significant input variables are selected to participate in the consequent of a rule. The proposed SEFC design method has been applied to different simulated control problems, including the cart-pole balancing system, a magnetic levitation system, and a water bath temperature control system. The proposed SEFC has been verified to be efficient and superior from these control problems, and from comparisons with some traditional GA-based fuzzy systems.
URI: http://dx.doi.org/10.1109/3477.836377
http://hdl.handle.net/11536/30612
ISSN: 1083-4419
DOI: 10.1109/3477.836377
期刊: IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
Volume: 30
Issue: 2
起始頁: 290
結束頁: 302
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