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遗传算法在模糊模型参数辨识中的应用
Application of genetic algorithm in parameter identification based on fuzzy model
【摘要】 介绍了T-S模糊模型的建模过程,在现有T-S模糊模型参数辨识方法的基础上,提出了一种先应用最小二乘法对结论参数进行粗略辨识,以确定参数的大致范围之后,再应用遗传算法对前提参数和结论参数同时优化的参数辨识方法。通过MATLAB对本算法进行了仿真,并对非线性函数进行了逼近实验,所取得的结果令人满意。
【Abstract】 The course of T-S fuzzy construct model was introduced,and an approach was proposed based on the research of T-S fuzzy model parameter identification.First,least square method was used to identify conclusion parameter in order to get the field of the par-ameter.Second,genetic algorithm was used to optimize the parameters.At last,the algorithm was realized by MATLAB program,and a nonlinear function was drawn up.The result is satisfactory.
【关键词】 最小二乘法;
参数辨识;
遗传算法;
MATLB;
仿真研究;
【Key words】 least square method; parameter identification; genetic algorithm; MATLB; simulation research;
【Key words】 least square method; parameter identification; genetic algorithm; MATLB; simulation research;
【基金】 山东省自然科学基金项目(2004ZX35);山东理工大学科研基金项目(03KJ16)
- 【文献出处】 计算机工程与设计 ,Computer Engineering and Design , 编辑部邮箱 ,2006年02期
- 【分类号】N945.14
- 【被引频次】10
- 【下载频次】202