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-2 | Engels |
|---|---|
| Pagina's (van-tot) | 86-91 |
| Aantal pagina's | 6 |
| Tijdschrift | IFAC-PapersOnLine |
| Volume | 58 |
| Nummer van het tijdschrift | 18 |
| DOI's | |
| Status | Gepubliceerd - 1 aug. 2024 |
| Evenement | 8th IFAC Conference on Nonlinear Model Predictive Control, NMPC 2024 - Kyoto, Japan Duur: 21 aug. 2024 → 24 aug. 2024 |
Bibliografische nota
Publisher Copyright:Copyright © 2024 The Authors.
Financiering
| Financiers | Financiernummer |
|---|---|
| European Union’s Horizon Europe research and innovation programme | 101055384 |
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