Abstract
In order to optimize the control quality of the air supply system aiming at its multi-disturbance, based on the historical operation data of the boiler air supply control system of a 300 MW unit, this paper adopts a two-stage identification method based on asymptotic theory and establishes an accurate model and simulation system of the air supply system. Based on the model established by asymptotic identification, we design a constrained Model Predictive Control with Kalman Filter state estimation and an Active Disturbance Rejection Control based on extended state disturbance observation two optimization schemes. The simulation based on field data shows that both schemes can be considered to possess comparatively higher practicability in the optimization of the air supply control system.
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