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Towards data-driven predictive control using wavelets
Publikationstyp
Conference Paper
Date Issued
2023-07-01
Sprache
English
Author(s)
Journal
Volume
56
Issue
2
Start Page
632
End Page
637
Citation
IFAC PapersOnLine 56 (2): 632–637 (2023)
Contribution to Conference
Publisher DOI
Scopus ID
ISBN
9781713872344
Recently, data-driven predictive control schemes based on the fundamental lemma by Willems et al. (2005) have received widespread research attention. However, the large and dense Hankel matrices appearing in the equality constraints of the underlying optimal control problem can lead to numerical complications. This paper tailors the fundamental lemma to LTI dynamics resulting from the application of the wavelet transform to input-output trajectory data. Directly using wavelet coefficients to construct Hankel matrices and to formalize the online optimization problem, we propose a data-driven predictive control scheme. Due to the down-sampling nature of the wavelet transform, the scheme is built around Hankel matrices of reduced size, which is advantageous for computations. Furthermore, in the presence of substantial measurement noise the wavelet transform is beneficial for closed-loop performance. We draw upon simulation examples to illustrate the efficacy of the proposed methodology.
Subjects
data-based control
Data-driven optimal control
predictive control
wavelet transform
DDC Class
004: Computer Sciences
620: Engineering