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提出了一种基于小波基西教神经网络的未知非线性系统的一步超前预测控制算法。该方法利用小波网络学习这个非线性系统，并且应用小波神经网络模型作为系统的预测模型。控制信号直接通过极小化期里输出值与预测输出位之间的偏差来获得。通过对一非线性系统的仿真，表明了该方法的有效性。
A new one-step predictive control algorithm for unknown nonlinear systems based on wavelet-based neural networks is proposed. This method uses the wavelet network to study this nonlinear system, and applies the wavelet neural network model as the prediction model of the system. The control signal is obtained directly from the deviation between the output value and the predicted output bit during the minimization period. The simulation of a nonlinear system shows the effectiveness of the method.