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模糊隶属度函数的遗传优化
Genetic Optimization of Fuzzy Membership Functions
【摘要】 模糊控制的成功应用依赖于一系列参数,例如隶属度函数,这些参数通常是主观设定的。该文提出了一种基于RGA的遗传优化算法来实现隶属度函数的生成和优化,克服了输入和输出变量隶属度函数参数设计的主观性和盲目性。通过在模糊控制器进行仿真比较研究,结果表明模糊控制器经过优化后控制品质有较大的改善和提高。
【Abstract】 The successful application of fuzzy control depends on some subjectively decided parameters,such as fuzzy membership functions.In this paper,a RGA based genetic algorithm was propose to optimize the fuzzy membership function’s parameters.The subjectivity and blindness were avoided by using this method in the process of designing the input and output membership functions.The optimized fuzzy logic controller has been compared with the traditional one and the results suggest that the control quality of the fuzzy logic controller is greatly improved.
【关键词】 模糊控制;
模糊隶属度函数;
遗传优化;
【Key words】 fuzzy control; fuzzy membership functions; genetic optimization;
【Key words】 fuzzy control; fuzzy membership functions; genetic optimization;
【基金】 浙江省自然科学基金资助项目(Y107706)
- 【文献出处】 杭州电子科技大学学报 ,Journal of Hangzhou Dianzi University , 编辑部邮箱 ,2009年04期
- 【分类号】TP18
- 【被引频次】32
- 【下载频次】724