Application of adaptive predictive functional control in boiler combustion system based on CARIMA model

As the boiler combustion system of thermal power plant has variable operating conditions with long time delay and deep coupling, an adaptive predictive functional control method based on CARIMA is presented for it, which applies the predictive model to forecast the system output of next step and takes the variation rate of the error between the set value and the predicted value as the input of the adaptive controller. The controller output is deduced by the least squares algorithm. When the parameters of the model for the object to be controlled are unknown or gradual-time-varying, the parameters of the predictive functional controller are amended in real time by the real-time parameter identification of process model to further improve the control quality and enhance the boiler combustion efficiency. Simulative results show that, the adaptive predictive functional control is of simple computation, strong robustness and adaptability and high control precision.