Data enabled Predictive Control of LPV systems

Taleb Bou Hamdan (1, 2) , Patrick Coirault (1) , Guillaume Mercère (1) , Thibault Dairay (2, 3)

1 LIAS [Poitiers] - Laboratoire d'informatique et d'automatique pour les systèmes
2 Michelin - Manufacture Française des Pneumatiques Michelin
3 CB - CB - Centre Borelli - UMR 9010

This paper introduces a data-enabled predictive control methodology designed for Linear Parameter Varying (LPV) systems. By leveraging a polytopic representation of the LPV system, we formulate Willem’s lemma to accommodate parameter variations. The system trajectory is predicted over a finite horizon using specific trajectories generated offline. A notable advantage of this approach is its independence from a priori knowledge of parametric variations. Simulation studies conducted on both a numerical example and a simulator of a calendering process governed by partial differential equations substantiate the effectiveness of this approach.

Keywords: Data enabled predictive control; Willem’s lemma; Linear Parameter Varying Systems

Domains: Automatic Control Engineering; Computer Science [cs]

Taleb Bou Hamdan, Patrick Coirault, Guillaume Mercère, Thibault Dairay. Data enabled Predictive Control of LPV systems. Control Engineering Practice, 2024, 149, ⟨10.1016/j.conengprac.2024.105969⟩. ⟨hal-04582708⟩