RBF neural network provides an effective means for system identification and modeling with its advantages of smaller calculation quantity and high learning speed.
R BF神经网络以其计算量小，学习速度快，不易陷入局部极小等诸多优点为系统辨识与建模提供了一种有效的手段。
Using RBF NN can restore the airplane to the normal state by online regulating the effect of the uncertainties and the error caused by fuzzy modeling.
采用RBF神经网络在线补偿不确定项和模糊建模误差，能够使飞机获得满意的控制效果。
Simulation results indicate that the modeling method by using the RBF neural network identification technique is effective with the established model featuring a relative high precision.
仿真结果表明采用RBF神经网络辨识建模的方法是有效的，建立的模型精度较高。
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