Title
Data-enabled predictive control with instrumental variables: the direct equivalence with subspace predictive control
Author
van Wingerden, J.W. (TU Delft Team Jan-Willem van Wingerden) 
Mulders, S.P. (TU Delft Team Jan-Willem van Wingerden)
Dinkla, R.T.O. (TU Delft Team Jan-Willem van Wingerden)
Oomen, T.A.E. (TU Delft Team Jan-Willem van Wingerden)
Verhaegen, M.H.G. (TU Delft Team Michel Verhaegen)
Date
2022
Abstract
Direct data-driven control has attracted substantial interest since it enables optimization-based control without the need for a parametric model. This paper presents a new Instrumental Variable (IV) approach to Data-enabled Predictive Control (DeePC) that results in favorable noise mitigation properties, and demonstrates the direct equivalence between DeePC and Subspace Predictive Control (SPC). The methodology relies on the derivation of the characteristic equation in DeePC along the lines of subspace identification algorithms. A particular choice of IVs is presented that is uncorrelated with future noise, but at the same time highly correlated with the data matrix. A simulation study demonstrates the improved performance of the proposed algorithm in the presence of process and measurement noise.
Subject
Instruments
Measurement uncertainty
Prediction algorithms
Mathematical models
Parametric statistics
Noise measurement
Predictive control
To reference this document use:
http://resolver.tudelft.nl/uuid:0464de02-5c28-40c2-b0af-bef38e0ab411
DOI
https://doi.org/10.1109/CDC51059.2022.9992824
Publisher
IEEE
Embargo date
2023-07-10
ISBN
978-1-6654-6761-2
Source
Proceedings of the IEEE 61st Conference on Decision and Control (CDC 2022)
Event
IEEE 61st Conference on Decision and Control (CDC 2022), 2022-12-06 → 2022-12-09, Cancún, Mexico
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Part of collection
Institutional Repository
Document type
conference paper
Rights
© 2022 J.W. van Wingerden, S.P. Mulders, R.T.O. Dinkla, T.A.E. Oomen, M.H.G. Verhaegen