以玻璃窑炉的温度系统作为控制对象，采用具有自学习能力的BP 神经网络与传统PID 相结合的智能控制算法对其实施控制，并利用Matlab 软件进行仿真。仿真结果表明，神经网络PID 控制器具有较高的精度和较强的适应性，可以获得满意的控制效果。关键词：BP 神经网络，PID，玻璃窑炉，温度控制Abstract：This thesis takes temperature system of glass furnace as research object，makes use of the intelligent control combining BP neural network with study ability and traditional PID control to implement its function, and uses the Matlab software to imitate reality. The result of simulation shows that the neural network PID control has the higher accuracy and stronger adaptability, can get satisfied control result.Keywords: BP neural network, PID, glass furnace, temperature control