Disturbance rejection tuning of a tracking multi-parametric predictive controller

Abstract

Multi-parametric model predictive control (mp-MPC) enables application of MPC controllers with low on-line computational demand and fast sampling by shifting the burden of optimization to the off-line controller design stage. Because the approach is limited to problems of relatively small \dimensions, it is most useful for low-level control application, where disturbance rejection properties are very important. This study explores important issues in the transition from mp-MPC theory to the implementation of an industrial controller, with emphasis on offset-free output feedback tracking and Kalman filter tuning. A case study on a two-input single-output system of pressure control in a vacuum chamber of a wire annealer is presented.