LIAS

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.