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arXiv · 1910.00608

Set-based MPC for discrete-time LTI systems with maximal domain of attraction and minimal predictive control horizon

Alejandro Anderson·Agustina D'Jorge·Alejandro H. González·Antonio Ferramosca·Marcelo Actis
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Abstract

This paper presents a novel set-based model predictive control for tracking, which provides the largest domain of attraction, even with the minimal predictive/control horizon. The formulation - which consists of a single optimization problem - shows a dual behavior: one operating inside the maximal controllable set to the feasible equilibrium set, and the other operating at the N-controllable set to the same equilibrium set. Based on some finite-time convergence results, asymptotic stability of the resulting closed-loop is proved, while recursive feasibility is ensured for any change of the setpoint. The properties and advantages of the proposal have been tested on simulation models.

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Alejandro Anderson, Agustina D'Jorge, Alejandro H. González, Antonio Ferramosca, Marcelo Actis. 2019-10-01. Set-based MPC for discrete-time LTI systems with maximal domain of attraction and minimal predictive control horizon. https://arxiv.org/abs/1910.00608

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