非线性系统的广义T-S模糊模型的研究  

Study on Generalized T-S Fuzzy Model in Nonlinear System

作　　者：胡莲君[1] 宋弘[1] 

机构地区：[1]四川理工学院机电工程系,四川自贡643000

出　　处：《昆明理工大学学报（理工版）》2006年第3期38-40,共3页Journal of Kunming University of Science and Technology(Natural Science Edition)

摘　　要：在获得广义T-S模型结构之后,往往通过参数辩识,确定模型参数,这样得到的模型不是最优或次最优的,鉴于这个问题,提出了基于遗传算法搜索广义T-S模型系统最优结构参数的方法,采用二进制编码与实数编码并存的距阵方式,获得最优或次最优模型.仿真结果表明了该方法的有效性,并且模糊规则少,精度高.After the structure of generalized T - S model is obtained, parameters of the model are gotten through parameters identifying. The model is not the optimum. The method of optimum structure parameters used to search generalized T - S model is put forward based on the genetic algorithm. The matrix with binary system and real number coding is adopted, and the better or best model is obtained. Finally, simulation shows that the method is effective and has few fuzzy rules and high precision.

关 键 词：非线性系统 遗传算法 模糊控制 

分 类 号：TP11[自动化与计算机技术—控制理论与控制工程]