基于BP神经网络的模糊PID风量控制

Fuzzy PID air volume control based on BP neural network

针对煤矿主风机通风系统多变量、非线性、时变滞后性等问题,提出一种基于BP神经网络的模糊PID算法。该算法综合神经网络、模糊控制与PID调节的各自优点,既具有神经网络的自学习和自适应能力,又具有模糊控制的非线性控制作用,同时兼备PID调节的广泛性。仿真结果表明,该算法的响应速度、稳态精度均优于传统的PID调节,取得比较理想的控制效果。

In veiw of the coal mine main fan ventilation system which is multivariable,nonlinear,time-varying log,a kind of fuzzy PID algorithm based on BP neural network is presented.The algorithm combines the advantages of neural network, fuzzy control and PID control,has the self-learning and adaptive ability of neural network,the nonlinear control function of fuzzy control,and the universality of PID regulation.The simulation result shows show that the algorithm is superior to the traditional PID control in the response speed and steady state accuracy,and achieves the ideal control effect.