Predictive Control Method for Multivariable Disturbance Rejection in Desulphurization Systems
Removing sulfur dioxide from flue gas is an indispensable part of flue gas treatment in coal-fired power plants.Due to the multivariable and strong coupling characteristics of desulfurization systems,it is difficult to accurately es-timate disturbances based solely on decoupling control or disturbance observers designed for the main diagonal elements.Especially when the model deviation is large,treating the coupling relationship between objects as disturbances often leads to deterioration of control effectiveness and difficulty in achieving the expected results.Therefore,this paper proposes a multivariable disturbance observer,which is based on a multivariable discrete state space model and combines historical operating data to estimate the previous disturbance and compensate for it.This disturbance observer can consider the coupling relationship between different channels,ensuring the accuracy and rationality of disturbance estimation.Then,the effectiveness of this method is verified through simulation.
power plant desulfurization systemmodel predictive controlmultivariable disturbance observer
万方数据
维普
