Multi-objective predictive control: application for an uncertain process

This paper deals with the application of the Multi Objective Generalized Predictive Control (MOGPC) to level control in a laboratory process. The major characteristic of the considered plant is that the manual draining vane can take many positions causing changes in plant dynamics and strong disturbances in the process. The controller is based on a set of Controlled Auto Regressive Integrated Moving Average (CARIMA) model. The Recursive Least Squares (RLS) algorithm is used to estimate each model parameters. The control law is obtained by minimizing a multi objective optimization problem. The weighting sum approach is considered to formulate the control problem as a single criterion optimisation one. The real time control system implementation confirms the opportunity of using the MOGPC scheme to an uncertainty system.