Loewner-based Data-driven Iterative Structured Control Design

TL;DR

This paper introduces a data-driven control design method that directly enforces closed-loop stability during the controller reduction process without needing preliminary instability estimation, using an iterative optimization approach.

Contribution

It proposes a novel iterative control design method embedding stability constraints directly into the data-driven optimization, avoiding preliminary instability estimation.

Findings

Successfully applied to numerical examples demonstrating stability enforcement.

Improved matching between reference model and closed-loop system.

Method avoids the need for system instability estimation.

Abstract

Stability enforcement remains a challenge in data-driven control paradigms, where no parametrised model of the system is available. For instance, the system's instabilities can be estimated in order to enforce a closed-loop stability constraint on the controller reduction step. In order to avoid this preliminary estimation of instabilities, this paper proposes to embed a closed-loop stability constraint in the design. To that extent, an optimization problem is formulated in order to improve matching between the reference model and the closed-loop while maintaining internal stability. The proposed iterative procedure to solve this problem is illustrated on two numerical examples.