污水处理系统溶解氧的BP-PID控制算法

BP-PID Control Algorithm for Dissolved Oxygen in Sewage Treatment System

针对污水处理系统中溶解氧含量波动较大难以控制的问题,提出了一种基于BP神经网络的PID控制器设计方法,并根据BP神经网络的结构和特点优化了控制器参数。基于BP神经网络的PID控制器能根据系统状态在线调整PID控制参数,使系统误差保持在较小范围内,且能使系统受到干扰时快速恢复到稳定状态。以溶解氧含量为控制对象,分别对常规PID控制器和基于BP神经网络的PID控制器进行了大量仿真研究。仿真结果表明:基于BP神经网络的控制系统具有较好的适应性和鲁棒性,其控制品质优于常规PID控制器。

Aiming at the problem that the dissipation of dissolved oxygen in the sewage treatment system is difficult to control,a PID controller design method based on BP neural network is proposed,and the controller parameters are optimized according to the structure and characteristics of BP neural network.The PID controller based on BP neural network can adjust the PID control parameters according to the system state,keep the system error in a small range,and can quickly restore the system to a steady state when it is disturbed.The PID controller and the PID controller based on BP neural network are studied by using the dissolved oxygen content as the control object respectively.The simulation results show that the control system based on BP neural network has better adaptability and robustness,and its control quality is superior to conventional PID controller.