Work

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

Year: 2026

Type: article

Abstract: 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.

Source: Axioms

DOI: 10.3390/axioms15020114

Authors: Hongli Yang, Qian Du, Ivan Ganchev Ivanov

Institutions: Qingdao Huanghai University, Shandong University of Science and Technology, Sofia University "St. Kliment Ohridski"

Language: English

Topic: Advanced Control Systems Optimization

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,896

Funder: Texas Space Grant Consortium