摘要
本文提出了一种新的自学习模糊控制算法。利用改进的ｐｉ－ｓｉｇｍａ神经网络，对模糊控制器的结论参数进行辨识，并不断修正隶属函数，实现了模糊规则的自动更新。这种方法被用于机器人解耦控制，取得了满意的仿真结果。
A novel self-organizing fuzzy controller is proposed in this paper.By use of the modified pi-sigma neural network, the controller is able to identify its consequent parameters and modify the membership functions on line, which makes it possible to update the fuzzy rules automatically. The novel controller is applied to decoupled control for robot manipulators and satisfying simulation results are obtained.
出处
《电工技术学报》
EI
CSCD
北大核心
1994年第4期35-40,共6页
Transactions of China Electrotechnical Society
基金
国家自然科学基金
关键词
自学习控制
机器人
模糊控制
神经网络
Self-organizing fuzzy control Artificial neural network Robot control Nonlinear decoupled control
