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arXiv · 2007.07139

Nonlinear MPC for Tracking for a Class of Non-Convex Admissible Output Sets

Andres Cotorruelo·Daniel R. Ramirez·Daniel Limon·Emanuele Garone
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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.

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Andres Cotorruelo, Daniel R. Ramirez, Daniel Limon, Emanuele Garone. 2020-07-14. Nonlinear MPC for Tracking for a Class of Non-Convex Admissible Output Sets. https://arxiv.org/abs/2007.07139

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