Identification and predictive control for a circulation fluidized bed boiler

This paper introduces the design and presents the research findings of the identification and control application for an industrial Circulation Fluidized Bed (CFB) boiler. Linear Parameter Varying (LPV) model is used in the model identification where steam flow is selected as the operation-point (scheduling) variable. Three kinds of weighting functions, namely linear, cubic splines and Gaussian functions are compared. LPV model based Model Predictive Control (MPC) is also simulated. Test results show that LPV model is more accurate than linear model, and LPV MPC yields a better control effect than linear MPC.

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