Fast identification and stabilization of unknown linear systems

TL;DR

This paper introduces a simple, model-free algorithm for stabilizing unknown linear systems using minimal samples by first identifying the system partially and then stabilizing its controllable part.

Contribution

The paper presents a novel, minimal-sample, model-free method for stabilizing unknown linear systems through partial identification and control of the stabilizable subsystem.

Findings

Effective stabilization with minimal samples

No prior model knowledge required

Applicable to stabilizable systems

Abstract

In the present work, a simple algorithm for stabilizing an unknown linear time-invariant system is proposed, assuming only that this system is stabilizable. The suggested algorithm is based on first performing a partial identification of the system and then stabilizing the controllable subsystem. It should be emphasized that our approach does not depend on any prior model knowledge and requires only a minimal number of samples.