神经网络自适应逆控制在铝电解过程控制中的应用

通过采用神经网络自适应逆控制方法来解决铝电解过程中存在的时变和大时滞问题,可以提高其控制性能。本文就铝电解过程进行建模,并将神经网络与自适应逆控制算法相结合,发现神经网络自适应逆控制模型的输出能很好地跟踪铝电解生产过程,控制效果好。在这里提出一个能使铝电解过程很快进入稳态、超调量较小的控制方案,提高铝电解过程的动态和稳态性能。

the Use of Neural Network Adaptive Inverse Control in Aluminum Electrolysis Process Control

Using neural network adaptive inverse control method can solve the problem of time variation and delay which exit in the aluminum electrolysis process. That can improve the control characteristics. This paper establishes the model of neural network, combines the neural network and adaptive inverse control algorithm, and realizes the optimize control of the aluminum electrolysis process. The simulation result shows the adaptive inverse control model can trace the aluminum electrolysis process .The result is good. The method presented in this paper can make the aluminum electrolysis process stable ,with low overshot and better dynamic and static performance.