GREY BOX MODELLING OF A PICKLING PROCESS USING TAYLOR SERIAL EXPANSION

This paper deals with a case study of grey box modelling where known parts are modelled using a priori information and unknown parts are described as general continuous nonlinear functions, which are approximated by means of Taylor series including higher order terms. In the Taylor series, the partial derivatives are estimated from measured data by minimising the maximum likelihood function. This approach is used to keep the number of estimated parameters low. The modelling procedure follows a structured approach including; basic modelling, data acquisition, model calibration, expanded modelling, stochastic modelling and model appraisal.