将人工神经网络的非线性特性和信息的分布性用于煤低温自燃实验炉的模型辩识。

The nonlinearity and distribution of information processing of the artificial neural network are utilized in the indentification of model of coal spontaneous combustion stove at low temperature.

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其主要特点是能够提供一个跟踪网络来辩识系统模型，进而确定控制器的网络参数，实现间接自适应神经网络控制。

Its major feature is that it can provide a tracing network to identify system model so as to determine the network parameters of the controller and realize an indirect adaptive neural network control.

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采用新型对角回归神经网络来辩识系统模型，可对PID控制器参数进行整定，实现多变量解耦控制。

Adopting new type diagonal regression neural network to identify the system model, the parameters of PID controller have been set, and the multi -variable decoupling control being realized.

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