基于模糊专家模型的神经控制器及应用研究

针对具有严重非线性特性的pH中和过程,提出了一种基于模糊专家模型的神经控制策略,这种方法将神经网络逆控制器与神经元PID控制器相结合,并利用模糊专家模型所得到的预报结果来调整神经元PID的权值。仿真试验表明该方法能有效改善控制性能,所提出的方法实现了对pH过程的有效控制,并且有很强的适应性。

Neural Controller Based on Fuzzy Expert Model and Research on Its Application

A neural control strategy based on fuzzy expert model is presented for pH neutralization process with severe nonlinearity. The scheme combined a neural network inverse controller with a neuron PID controller, and used the forecast results of the fuzzy expert model to adjust the weights of the neuron PID controller. The simulated results show that this method offers effective improvement of control performance and implementation of control on a pH process. The method features high adaptability.