CONTROL OF A PICKLING PROCESS USING A GREY BOX MODEL

This paper deals with model predictive control using a grey box model. The process is 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. The grey box model is used to design and tune a model predictive controller to control the pickling process. The process is a bottle neck in the production line and the simulation shows that the production can be increased approximately 15 % by using the controller.