Work

A continuous-time fundamental lemma and its application in data-driven optimal control

Year: 2024

Type: article

Abstract: Data-driven control of discrete-time and continuous-time systems is of tremendous research interest. In this paper, we explore data-driven optimal control of continuous-time linear systems using input-output data. Based on a density result, we rigorously derive error bounds for finite-order polynomial approximations of elements of the system behavior. To this end, we leverage a link between latent variables and flat outputs of controllable systems. Combined with a continuous-time counterpart of Willems et al.’s fundamental lemma, we characterize the suboptimality resulting from polynomial approximations in data-driven linear-quadratic optimal control. Finally, we draw upon a numerical example to illustrate our results.

Source: Systems & Control Letters

DOI: 10.1016/j.sysconle.2024.105950

Authors: Philipp Schmitz, Timm Faulwasser, Paolo Rapisarda, Karl Worthmann

Language: English

Topic: Control Systems and Identification

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,830

Funders: Carl-Zeiss-Stiftung, Deutsche Forschungsgemeinschaft

Awards: Optimierungsbasierte Steuerung und Regelung, G434514500