Nonlinear MPC for Tracking for a Class of Non-Convex Admissible Output Sets
Systems and Control
2020-07-15 v1 Systems and Control
Abstract
This paper presents an extension to the nonlinear Model Predictive Control for Tracking scheme able to guarantee convergence even in cases of non-convex output admissible sets. This is achieved by incorporating a convexifying homeomorphism in the optimization problem, allowing it to be solved in the convex space. A novel class of non-convex sets is also defined for which a systematic procedure to construct a convexifying homeomorphism is provided. This homeomorphism is then embedded in the Model Predictive Control optimization problem in such a way that the homeomorphism is no longer required in closed form. Finally, the effectiveness of the proposed method is showcased through an illustrative example.
Keywords
Cite
@article{arxiv.2007.07139,
title = {Nonlinear MPC for Tracking for a Class of Non-Convex Admissible Output Sets},
author = {Andres Cotorruelo and Daniel R. Ramirez and Daniel Limon and Emanuele Garone},
journal= {arXiv preprint arXiv:2007.07139},
year = {2020}
}