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溶解氧控制是污水处理厂控制的关键,针对当前溶解氧控制效率低下的问题,提出了一种具有自学习和自适应功能的模糊PID神经网络算法。首先建立PID模糊控制规则表;然后采用神经网络对模糊控制规则表进行不断的训练,得到最佳的模糊控制规则表;最后利用Matlab仿真和工程模拟调试进行验证。结果表明,在大滞后非线性的曝气控制系统中,模糊PID神经网络算法能在最短的时间内使溶解氧达到所期望的值,且整个控制过程具有良好的动态性能和稳态性能。
Dissolved oxygen control is the key of sewage treatment plant control. Aiming at the problem of low efficiency of dissolved oxygen control, a fuzzy PID neural network algorithm with self-learning and self-adaptive function is proposed. Firstly, the PID fuzzy control rules table is established. Then the neural network is used to continuously train the fuzzy control rules table to get the best fuzzy control rules table. Finally, the simulation is carried out by Matlab simulation and engineering simulation debugging. The results show that in a large delay nonlinear aeration control system, the fuzzy PID neural network algorithm can reach the desired value in the shortest time, and the whole control process has good dynamic performance and steady performance.