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Frequency-Domain Data-Driven Predictive Control

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Samenvatting

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.

Originele taal-2Engels
Pagina's (van-tot)86-91
Aantal pagina's6
TijdschriftIFAC-PapersOnLine
Volume58
Nummer van het tijdschrift18
DOI's
StatusGepubliceerd - 1 aug. 2024
Evenement8th IFAC Conference on Nonlinear Model Predictive Control, NMPC 2024 - Kyoto, Japan
Duur: 21 aug. 202424 aug. 2024

Bibliografische nota

Publisher Copyright:
Copyright © 2024 The Authors.

Financiering

FinanciersFinanciernummer
European Union’s Horizon Europe research and innovation programme101055384

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