Work

Data-based regional stabilization of linear systems with saturating actuators

Year: 2025

Type: article

Abstract: Data-based asymptotic stabilization of unknown discrete-time linear systems with saturating actuators is addressed. The proposed approach relies on an explicit sector-bounded representation of the closed-loop system built from noisy state-input data. Relying on this novel representation, sufficient conditions in the form of linear matrix inequalities are established to ensure closed-loop regional asymptotic stability. These conditions are used to formulate a convex optimal controller design that allows one to maximize the region of attraction.Two numerical examples illustrate the applicability of the proposed results.

Source: Automatica

DOI: 10.1016/j.automatica.2025.112642

Authors: Francesco Ferrante, Mirko Leomanni, Gabriele Costante, Francesco Crocetti, Mario Luca Fravolini

Institution: University of Perugia

Language: English

Topic: Stability and Control of Uncertain Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,760

OpenAlex ID: W4415218171

FWCI:

Cites: 24

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