BP神经网络PID控制器在主汽温控制中的应用

Study on PID controller based on BP neural network in main steam temperature control

电厂锅炉主蒸汽温度对汽轮机的使用寿命和机组的运行安全有重要影响,电厂锅炉主蒸汽温度动态特性随着负荷的变化而变化,如何把主蒸汽温度快速稳定的控制在设定值附近是火电厂热工过程控制的难点之一。针对电厂锅炉在不同负荷下的主蒸汽温度控制问题,提出一种基于BP神经网络的PID串级控制方案,神经网络通过对系统的不断学习,加权系数不断调整的方式,使PID控制器参数实现最佳的组合,仿真实例验证了所提方法具有较好的控制品质和较强的抗干扰能力。

The main steam temperature of power plant boiler has an important effect on the service life, securi- ty of the whole unit. As the load changes, the dynamics of the main steam temperature of power plant boiler changes. One of the difficulties in the heat-engine plant process control is about how to get the main steam temperature near the set point quickly. Focusing on the control of main steam temperature of the boiler unite under different loads, the writer proposes PID cascade control scheme based on BP Neural Network. Neural network obtains the best combination among PID controller＇ s parameters through learning on system and the adjustment of weighting coefficient, and the simulation example verifies that the proposed method has better control quality and high anti-disturbing ability.