Abstract
Wide and complex process models set challenges to the modelling work. Especially the determination and tuning of the parameters of complex models are often laborious and time-consuming. The strong cross-interconnection of modelled variables also makes tuning work more difficult. Efficient tuning tools can be used to accelerate tuning work. In this paper it is proposed how a nonlinear multivariable optimisation method can be adapted for the tuning of the parameters of a dynamic circulating fluidized bed (CFB) drum boiler model, which based on the first principle laws of mass and energy. In the fine-tuning example, the tuneable variables are the gas side heat transfer coefficients and the water side local resistance coefficients of the heat exchanger model blocks into the flue gas duct.
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