基于遗传算法的动态模糊模型辨识非线性系统方法  

New Method of Dynamic Fuzzy Identification Based on Genetic Algorithm in Nonlinear System

作　　者：吴刚[1] 童朝南[1] 孙一康[1] 

机构地区：[1]北京科技大学自动控制研究所,北京100083

出　　处：《北京科技大学学报》1999年第3期301-303,共3页Journal of University of Science and Technology Beijing

摘　　要：针对复杂的动态系统，提出了一种基于遗传算法的模糊模型辨识方法，给出了学习模糊规则的新算法，探讨模糊推理方法和遗传学习算法用于非线性系统建模的问题．仿真结果证明了该算法的有效性．Aimed at complex dynamic systems, a new method of dynamic fuzzy identification based on Genetic Algorithm is proposed. A new algorithm for learning fuzzy rules is given. Fuzzy inference systems and genetic learning algorithm are discussed to nonlinear system modeling .The simulation results show that this method has good effectiveness.

关 键 词：非线性系统 遗传算法 模糊模型辨识 模糊推理 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程] TP271.72[自动化与计算机技术—控制科学与工程]