本文给出一种在线学习RBF神经网络的快速算法，并设计了在线学习RBF神经网络的MARAC。通过仿真表明，在线RBF神经网络的MRAC计算量小、在线学习、跟踪时间短、控制精度高的优点。%This paper presents the fast algorithm of the on-line learning RBF neural networks, and design the model reference adaptive controller of on-line RBF neural networks. The present algorithm have less computational cost, on-line learning, shorter training times and considerable control accuracy by the simulation results for the model reference adaptive controller.
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