基于SOTSFNN的溶解氧浓度控制方法

摘要

It is difficult to control the dissolved oxygen concentration of the wastewater treatment, a novel approach of control method based on the self-organizing T-S fuzzy neural network (SOTSFNN) is proposed. The essence of the approach according to the actual environment adjust the neuron self-adaptation in time, based on the activity intensity comparisons of the fuzzy rules layer, and construct the appropriate control structure, thus increase the accuracy of control effect. Meanwhile, the parameters of the controller are adjusted on line using error back propagation algorithm. Finally, the controller is applied to Benchmark Simulation Model No.1. The results indicate that the proposed SOTSFNN controller can achieve better control effect for dissolved oxygen concentration with good adaptability.%针对污水处理过程溶解氧浓度难以控制的问题，提出了一种基于自组织T-S模糊神经网络的控制方法。其实质是采用模糊规则层激活强度的方法，根据实际环境自适应的对神经元进行调整，构造合适的控制结构，从而提高控制精度。同时采用梯度下降法对控制器的各个参数进行实时调整。该控制器运用在污水处理基准仿真模型中进行实验，结果表明，提出的SO-TSFNN控制方法能够较好地实现对溶解氧浓度的控制，具有较好的自适应性。