T-S型模糊RBF神经网络多变量自适应控制器的研究

On the T-S Fuzzy RBF Network Multi-variable Adaptive Controller

提出ＴＳ型模糊ＲＢＦ神经网络模型，并将该网络模型应用于多变量控制系统，构成多变量自适应控制器．同时对网络结构和参数的学习算法及网络参数的在线自学习算法进行研究．仿真结果表明本文提出的学习方法是有效的。

A new type of Takagi-Sugeno(T-S) fuzzy radial basis function (RBF) neural network was proposed and applied to multi-variable control. The cluster algorithm of parameters and structure of the network and the online self-learning algorithm were also discussed. Simulation results indicate that these algorithms are effective and the T-S fuzzy RBF network controller has good adaptability.