Frequency-Domain Data-Driven Predictive Control

TL;DR

This paper introduces a frequency-domain data-driven predictive control scheme that leverages frequency data of the plant, extending DeePC methods and demonstrating its effectiveness through a numerical case study.

Contribution

It develops a novel frequency-domain version of Willems' lemma and a predictive control scheme that complements existing time-series based approaches.

Findings

FreePC is equivalent to DeePC under certain conditions.

The scheme effectively utilizes frequency-domain data for control.

Numerical case study demonstrates its practical viability.

Abstract

In this paper, we propose a data-driven predictive control scheme based on measured frequency-domain data of the plant. This novel scheme complements the well-known data-driven predictive control (DeePC) approach based on time series data. To develop this new frequency-domain data-driven predictive control (FreePC) scheme, we introduce a novel version of Willems' fundamental lemma based on frequency-domain data. By exploiting frequency-domain data, we allow recent direct data-driven (predictive) control methodologies to benefit from the available expertise and techniques for non-parametric frequency-domain identification in academia and industry. We prove that, under appropriate conditions, the new FreePC scheme is equivalent to the corresponding DeePC scheme. The strengths of FreePC are demonstrated in a numerical case study.