摘要
针对模糊辨识器的参数优化，提出了将改进的遗传算法（ＭＧＡ）应用于模糊辨识器的离线学习，并在此基础上采用ＢＰ算法对其参数在线调整，实现了非线性动态系统模糊辨识。解决了输入仅为一维语言变量时，模糊辨识器的实现问题。仿真结果证实了该方法的有效性。
In order to optimize parameters of fuzzy identifier, this paper proposes a scheme, which deals with the off-line analysis of fuzzy identifier by MGA. BP-algorithm is employed to implement the fuzzy identification of nonlinear dynamic system.When input is one language variable, this scheme is proved to be realizable. The simulation results are also given in this paper.
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2000年第2期170-173,共4页
Journal of University of Electronic Science and Technology of China
基金
安徽省自然科学基金!99J10168
关键词
模糊辨识器
动态系统辨识
非线性
遗传算法
fuzzy identifier
dynamic system identification
genetic algorithm
BP algorithm
