采用将BP神经网络的学习算法应用于PID控制中，使BP神经网络与PID控制算法结合起来，通过吸收两者的优势，使系统具有自适应性。这样系统可自动调节控制参数，更好地适应输入变量的变化，提高控制性能和可靠性。本文从BP神经网络的基本构成原理、学习规则和学习算法出发，设计了基于BP神经网络的PID控制器，并对其进行了仿真分析,结果表明，该控制方案可行、有效。-We apply the learning algorithm of BP neural network to the PID control, making the BP neural network and the PID control algorithm combined, and we enable the system to auto-adapted through absorbs superiority of both, and then the system can make control parameters adjusted of itself to adapt the change of input variable, enhance the control performance and the reliability. This article embarked from the BP neural network s basic constitution principle, the study rule and the learning algorithm，designed PID controller that based on the BP neural network, and carried on the simulation analysis to it, the result of simulation indicated that the control plan is feasible and effective.