多变量发酵过程的神经网络在线解耦控制

Online Decoupling Control of Neural Network in a Multi-variable Fermentation Process

  • 摘要: 为提高多变量系统解耦控制的性能,提出了一种基于参考模型的神经网络在线解耦控制方法.构造神经网络实现前馈解耦,通过参考模型的输出与被控系统输出估计耦合作用对被控量的影响,由此设计神经网络权值参数学习算法,在线调整网络参数使多变量耦合系统实现解耦;对解耦后的子系统分别设计闭环控制器,以达到优良的控制性能. 仿真实验结果表明,提出的解耦控制方法是简单有效的.

     

    Abstract: To improve the decoupling control performance for multivariable system, a online decoupling control method of neural network based on reference model is proposed. Neural network is constructed to implement feedforward decoupling. Estimate the effect of coupled function on controlled value according to the outputs of reference model and controlled system. Then a learning algorithm of neural network weights parameter is designed and used to adjust the parameters of neural network on-line. The close loop controllers for the decoupling system are designed and the good control performance is achieved. The simulation experiments show the proposed decoupling control method is simple and effective.

     

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