Application of improved implicit generalized predictive control in main steam pressure of gas-fired power generation boiler

Abstract

Aiming at the problems of non-linearity and variable model parameters of the main steam pressure control system of gas-fired power generation boiler, an improved implicit generalized predictive control strategy was proposed. First, the forgetting factor recursive least square method was used to identify the model parameters, and a discrete mathematical model of the main steam pressure was established. Second, an implicit generalized predictive control system for main steam pressure was established on the basis of conventional generalized predictive control theory, which simplified the control algorithm and improved the robustness of the system by adding a PI structure to the objective function. The simulation results show that, compared with the cascade PID and conventional implicit generalized predictive control, the proposed control strategy reduces the adjustment time by 20 s at most when the model is adapted; the overshoot decreases by up to 5.08% and the adjustment time decreases by up to 36 s when the model is mismatched, and the system robustness and anti-interference ability are improved. The engineering application shows that the main steam pressure control deviation is within ±0.2 MPa, and the control accuracy is significantly improved in the proposed strategy. The improved implicit generalized predictive control has high research and application value in the main steam pressure control in industrial production.

Keywords

• system identification; gas-fired power generation boiler; main steam pressure; forgetting factor recursive least squares method; implicit generalized predictive control