A scheduled controller for a nonlinear process of Wiener type based on IMC framework and local models
In this paper, we present an efficient, practical gain scheduled controller for a nonlinear process of Wiener type, pH problem. The main idea is to use locally linearized first-order models to approximate the real process in the neighborhood of steady points, thus resulting in a conventional PI controller within IMC framework. The scheduling variable is chosen to be the measured pH value which is supposed to be at steady state. Once locally linearized first-order models at several steady points are obtained, a simple linear interpolation is carried out for those points in between them. The results show that the practical scheme used can perform satisfactorily.
nonlinear process local model gain scheduled controller