Development of a Model Predictive Controller for an Unstable Heavy Self-Balancing Robot

Abstract

This paper describes development of a control system for a heavy self-balancing two-wheeled robot. The development process includes: model identification, model tuning, design and tuning of a Model Predictive Control (MPC) algorithm. Although a simple linear state-space model with only two state variables is used, the results of laboratory experiments clearly indicate that the MPC algorithm based on such a model works well, i.e. the algorithm is able to effectively stabilise the robot.