Data-Driven Structured Control for Continuous-Time LTI Systems

TL;DR

This paper presents a data-driven approach to designing structured controllers for continuous-time LTI systems, enabling stabilization and performance optimization using minimal data and iterative algorithms.

Contribution

It introduces a novel method to incorporate structural constraints into data-driven control design for continuous-time LTI systems.

Findings

Effective stabilization and performance control demonstrated

Minimal data suffices for controller synthesis

Iterative algorithms improve control performance

Abstract

This paper addresses the data-driven structured controller design problem for continuous-time linear time-invariant (LTI) systems. We consider three control objectives, including stabilization, $H_2$ performance, and $H_\infty$ performance. Using the collected data, we construct a minimal matrix ellipsoid that contains all admissible system matrices. We propose some linearization techniques that enable us to incorporate the structural constraint on the controller, which motivates an iterative algorithm for each control objective. Finally, we provide some numerical examples to demonstrate the effectiveness of the proposed methods.