會議論文
| 學年 | 83 |
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| 學期 | 2 |
| 發表日期 | 1995-03-01 |
| 作品名稱 | A GA-based fuzzy controller with sliding mode |
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| 著者 | Lin, Sinn-cheng; Chen, Yung-yaw |
| 作品所屬單位 | 淡江大學資訊與圖書館學系 |
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| 摘要 | In this study, the genetic algorithms are applied to find out a nearly optimal fuzzy rule-base for fuzzy sliding mode controller in the sense of fitness. In conventional fuzzy logic controllers (FLC), linearly increasing m either input variables or input linguistic labels would lead the number of rules grow up exponentially. Since the larger size of rule base would cause the longer string length and higher computing load, it becomes one of the difficulties of realizing genetic algorithms to search the suitable rules or membership functions for fuzzy logic controllers. This paper will show that the number of rules in fuzzy sliding mode controller (FSMC) is a linear function of input variables, such that the inferring load of the inference engine in FSMC is more light than that of FLC, and the string length of unknown parameters in FSMC is shorter than that in FLC. Therefore. using genetic algorithms to search fuzzy rules or membership functions for FSMC becomes more economical and applicable. The simulation results veri@ the efficiency of proposed approach. |
| 關鍵字 | Fuzzy logic control;Fuzzy sliding mode control;Genetic algorithm |
| 語言 | en |
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| 出處 | International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium, Yokohama, Japan |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/53600 ) |