This article presents the real-time implementation of the model predictive control for tracking formulation to control a two-wheeled inverted pendulum robot. This formulation offers several advantages over standard MPC formulations at the expense of the addition of a small number of decision variables, which complicates the inner structure of the matrices of the optimization problem. We implement a sparse solver, based on an extension of the alternating direction method of multipliers, in the system's embedded hardware. The results indicate that the solver is suitable for controlling a real system with sample times in the range of milliseconds using current, readily-available hardware.
@article{arxiv.2103.14571,
title = {Real-time implementation of MPC for tracking in embedded systems: Application to a two-wheeled inverted pendulum},
author = {Pablo Krupa and Jose Camara and Ignacio Alvarado and Daniel Limon and Teodoro Alamo},
journal= {arXiv preprint arXiv:2103.14571},
year = {2021}
}