模糊PID和Hopfield神经网络在矿井通风系统中的应用

Application of fuzzy PID and Hopfield neural network in mine ventilation system

针对传统的PID控制或者单一的模糊控制无法准确控制矿井通风系统风量的问题,提出了一种采用模糊PID调节器和Hopfield神经网络调节器对矿井通风机的转速、风门、风量进行控制的方法。该方法利用模糊控制器对PID参数进行实时修正,并结合Hopfield神经网络的联想记忆功能和反馈调节特性,实现矿井通风机风量的快速、稳定输出。仿真与实验结果表明,模糊PID调节器和Hopfield神经网络调节器可以准确控制矿井通风机的转速和风量,实现通风系统的稳定输出。

In view of problem that traditional PID control and single fuzzy control cannot control air flow of mine ventilation system accurately,the paper proposed a control method for rotational speed,air door and air flow of mine ventilator by using fuzzy PID regulator and Hopfield neural network regulator.The method employs fuzzy controller to correct PID parameters real-timely and combines association memory function and feedback regulation performance of Hopfield neural network,so as to realize quick and steady output of mine ventilator.The results of simulation and experiment show that the fuzzy PID regulator and Hopfield neural network regulator can control rotational speed and air flow of mine ventilator accurately and realize steady output of ventilation system.