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Data-driven MPC of descriptor systems : a case study for power networks
Publikationstyp
Conference Paper
Date Issued
2022
Sprache
English
Author(s)
Journal
Volume
55
Issue
30
Start Page
359
End Page
364
Citation
IFAC-PapersOnLine 55 (30): 359-364 (2022)
Contribution to Conference
Publisher DOI
Scopus ID
Publisher
Elsevier
Recently, data-driven predictive control of linear systems has received wide-spread research attention. It hinges on the fundamental lemma by Willems et al. In a previous paper, we have shown how this framework can be applied to predictive control of linear time-invariant descriptor systems. In the present paper, we present a case study wherein we apply data-driven predictive control to a discrete-time descriptor model obtained by discretization of the power-swing equations for a nine-bus system. Our results show the efficacy of the proposed control scheme and they underpin the prospect of the data-driven framework for control of descriptor systems.
Subjects
Data-driven control
descriptor systems
MPC
optimal control
power-swing equations
power systems
Willems' fundamental lemma
DDC Class
004: Computer Sciences
333.7: Natural Resources, Energy and Environment