模糊神经网络局部通风机调速控制器

Speed controller design of local fan based on fuzzy neural network

为提高煤矿局部通风机的调速能力,采用模糊控制与神经网络技术,设计了局部通风机智能调速控制器。该控制器由瓦斯检测、风速检测、模糊神经网络控制器、变频调速器和局部通风机五部分组成,采用多层前向神经网络输出控制量。仿真结果表明:通风机速度曲线与实际电机速度曲线误差很小,模糊控制与神经网络的结合能够克服传统线性和非线性控制的缺点,较好地实现煤矿局部通风机的调速,提高了系统的鲁棒性。

This paper is an attempt to improve the speed-regulating capacity of the local fan by designing the intelligent local fan speed controller using the technology of fuzzy control and neural network.The controller is composed of gas detection,speed detection,fuzzy neural network controller,variable-frequency governor and the local fan.Meanwhile an multilayer feedforward neural network is used to control the output.Simulation results show that there exists a very small error between the desired speed and the actual speed, so that the combination of fuzzy control and neural networks allows the conventional shortcomings in linear and nonlinear control to be eliminated, with resultant regulation of local fan speed and improvement in the system robustness.