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

作　　者：张景元[1] 

机构地区：[1]山东理工大学计算机科学与技术学院,山东淄博255049

出　　处：《计算机工程与设计》2006年第2期262-264,271,共4页Computer Engineering and Design

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)

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。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 

分 类 号：TP273.4[自动化与计算机技术—检测技术与自动化装置]