依据小波的非线性逼近能力和神经网络的自学习特性，提出了一种基于小波神经网络模型的自校正控制算法。
Based on the learning characteristic of neural network and the function approximation ability of the wavelet, a new self tuning control algorithm is presented.
仿真研究表明，只要恰当地选择神经网络正、逆模型的结构和辨识数据的长度等参数，实现加热炉神经网络内模自校正控制的结果是令人满意的。
Simulation shows that if chosen the appropriate ANN structure and training data quantity, its ANN internal model self-tuning control can be realized and the results can be acceptable.
建立了一种新型的神经网络自校正预测控制器，可有效地控制复杂的多变量非线性系统。
We present a new neural net based self tuning control which can effectively control complicated multivariable nonlinear systems.
建立了一种新型的神经网络自校正预测控制器，可有效地控制复杂的多变量非线性系统。
We present a new neural net based self tuning control which can effectively control complicated multivariable nonlinear systems.
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