A Heuristic Approach for Tuning Model Predictive Controller

This paper presents the results of a heuristic approach for tuning an embedded model predictive control (MPC) in real-time conditions. A gaseous pilot plant, a kind of interacting series processes, is used as the controlled process. Process modeling in this MPC uses gray-box approach, where two multi-input single-output (MISO) models are combined into a multi-input multi-output (MIMO) model. A real-time embedded control system consisting the off-the-shelf components and software tools is implemented and analyzed experimentally. Four tuning parameters are investigated to illustrate the easy and intuitively understandable MPC tuning rules. The aim here is to deliver an intuitive MPC tuning implementation that necessary to be considered in practical applications.