延迟时间未知的时延系统神经网络补偿控制

提出了延迟系统及延迟时间参数的神经网络辨识方法。改变神经网络输入样本区间，利用网络输出期望值与输出实际值之间的误差平方和产生的突变，可以辨识出非线性对象的延迟时间。将神经网络大延迟系统的辨识与基于模型补偿的控制策略相结合，可以用于具有变化参数或者不确定性延迟时间的大延迟系统的控制。仿真结果表明这种神经网络模型补偿延迟系统控制具有很好的控制效果，它是大延迟控制中克服延迟时间变化的很有希望的方法。

Neural networks compensate control for unknown systems with time delay

A neural network discrimination method for time delay system and the parameter of delay time is discussed. Using the abrupt mutation resulted from the training error sumsquare of the real output and the expected output of the network, this control method changes the input sample period of the neural network so that it can discriminate the delay time of the non linear model. Combining the discrimination of neural network system with long time delay and the control method based on model compensation, it can be applied to the control of the long time delay system with variable parameters or with unknown delay time. The results of the simulation show that the control of system with time delay based on neural network model compensation method has a very good control effect.