| 基于遗传算法的广义Takagi-Sugeno模糊逻辑系统最优参数辨识 |
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| 引用本文： | 李合生,毛剑琴,代冀阳.基于遗传算法的广义Takagi-Sugeno模糊逻辑系统最优参数辨识[J].自动化学报,2002,28(4):581-586. |
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| 作者姓名： | 李合生 毛剑琴 代冀阳 |
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| 作者单位： | 1.北京航空航天大学第七研究室,北京; |
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| 基金项目： | 北京市自然科学基金 ( 4992 0 0 7)资助 |
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| 摘 要： | 针对Takagi-Sugeno模糊逻辑系统的隶属函数不具有自适应性且模糊规则数的确定
带有很大的人为主观性,这里引入了一类广义Takagi-Sugeno模糊逻辑系统;在模型实现上，以
广义Takagi-Sugeno模型为个体,采用简单、有效的矩阵编码方式,借助遗传算法得到一个次优
的广义Takagi-Sugeno模糊系统模型,该模型不仅能很好地逼近所要辨识的非线性系统,而且
还具有较低的复杂度.仿真结果表明了广义Takagi-Sugeno模型及其参数辨识方法的正确性和
有效性.
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| 关 键 词： | 模糊逻辑系统 遗传算法 矩阵编码 参数辨识 |
| 收稿时间： | 2000-3-22 |
| 修稿时间： | 2000年3月22日 |
GENERALIZED TAKAGI-SUGENO FUZZY LOGICAL SYSTEM OPTIMAL PARAMETER IDENTIFICATION BASED ON GENETIC ALGORITHM |
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| LI He-Sheng,Mao Jian-Qin,Dai Ji-Yang.GENERALIZED TAKAGI-SUGENO FUZZY LOGICAL SYSTEM OPTIMAL PARAMETER IDENTIFICATION BASED ON GENETIC ALGORITHM[J].Acta Automatica Sinica,2002,28(4):581-586. |
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| Authors: | LI He-Sheng Mao Jian-Qin Dai Ji-Yang |
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| Affiliation: | 1.The Seventh Research Division,Beijing University of Aeronautics and Astronautics,Beijing;The Institute of Electric Engineering,Chinese Academy of Engineering Physics,Mianyang |
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| Abstract: | In Takagi-Sugeno fuzzy logical system, its membership functions have no self-adaptability and the number of fuzzy ruels is defined subjectively. In this paper, a generalized Takagi-Sugeno fuzzy logical system model is quoted. In search of optimal parameters of the generalized Takagi-Sugeno model the matrix coding is adopted. The structure of the generalized Takagi-Sugeno model is evolved by GA and the resulting suboptimal solution can be found quickly, which has lower complexity and approximates to a nonliner system very well. The validity of this method has been demonstrated by a numerical simulation. |
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| Keywords: | Fuzzy logical system genetic algorithm matrix coding parameter identification |
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