基于数据驱动的主汽温度改进灰色预测PID控制

An Improved Data-Driven Grey-Predictive PID Control for Main Steam Temperature

针对火电厂主蒸汽温度过程存在的大迟延和时变性等问题,本文提出了一种基于数据驱动的序列-残差联合灰色预测的串级PID控制策略。序列-残差联合灰色模型GM(1,1)是先采用常规灰色模型GM(1,1)对测量值进行预测,对预测残差作二次预测并用来修正常规灰色预测结果。将该策略应用于主汽温系统的串级PID控制,仿真结果表明,本文方法提高了系统的控制品质。

In order to deal with large time delay and nonlinearity of the main steam temperature process,this paper proposes a data-driven PID control strategy with sequence-residual grey model. The sequence-residual grey model GM（ 1,1） is based on the combination of conventional grey model GM（ 1,1） and residual grey model GM（ 1,1）. The strategy is applied to the main steam temperature control system. The input of the PID controller is the residual value between the model prediction value and the given value. The simulation results show that the adopted control strategy is effective.