Data-Driven Safe Controller Design for LPV Systems with Constant Input Matrix Under Polyhedral and Ellipsoidal Constraints

This paper proposes a data-driven control design framework for linear parameter-varying (LPV) systems with polyhedral and ellipsoidal constraints, where the input matrix of the system is constant. In contrast to traditional model-based approaches, the proposed method ensures closed-loop stability and safety invariance solely through measured data, eliminating the need for explicit system identification. For polyhedral constraints, a sufficient condition is given to ensure the λ-contractivity of perturbed LPV systems. Under ellipsoidal constraints, input limitations are incorporated through a linearization approach, which allows the λ-contractivity property of LPV systems to be verified using linear matrix inequalities (LMIs). Numerical examples demonstrate the effectiveness of the proposed method.