Constrained optimal reduced-order models from input/output data

Giordano Scarciotti, Zhong-Ping Jiang, Alessandro Astolfi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Model reduction by moment matching does not preserve, in a systematic way, the transient response of the system to be reduced, thus limiting the use of this model reduction technique in control problems. With the final goal of designing reduced-order models which can effectively be used (not just for analysis but also) for control purposes, we determine, using a data-driven approach, an estimate of the moments and of the transient response of an unknown system. We compute the unique, up to a change of coordinates, reduced-order model which possesses the estimated transient and, simultaneously, achieves moment matching at the prescribed interpolation points. The error between the output of the system and the output of the reduced-order model is minimized and we show that the resulting system is a constrained optimal (in a sense to be specified) reduced-order model. The results of the paper are illustrated by means of a simple numerical example.

Original languageEnglish (US)
Title of host publication2016 IEEE 55th Conference on Decision and Control, CDC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7453-7458
Number of pages6
ISBN (Electronic)9781509018376
DOIs
StatePublished - Dec 27 2016
Event55th IEEE Conference on Decision and Control, CDC 2016 - Las Vegas, United States
Duration: Dec 12 2016Dec 14 2016

Other

Other55th IEEE Conference on Decision and Control, CDC 2016
CountryUnited States
CityLas Vegas
Period12/12/1612/14/16

Fingerprint

Reduced Order Model
Moment Matching
Output
Transient Response
Model Reduction
Change of coordinates
Transient analysis
Data-driven
Control Problem
Limiting
Interpolate
Moment
Unknown
Numerical Examples
Interpolation
Estimate

ASJC Scopus subject areas

  • Artificial Intelligence
  • Decision Sciences (miscellaneous)
  • Control and Optimization

Cite this

Scarciotti, G., Jiang, Z-P., & Astolfi, A. (2016). Constrained optimal reduced-order models from input/output data. In 2016 IEEE 55th Conference on Decision and Control, CDC 2016 (pp. 7453-7458). [7799420] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2016.7799420

Constrained optimal reduced-order models from input/output data. / Scarciotti, Giordano; Jiang, Zhong-Ping; Astolfi, Alessandro.

2016 IEEE 55th Conference on Decision and Control, CDC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 7453-7458 7799420.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Scarciotti, G, Jiang, Z-P & Astolfi, A 2016, Constrained optimal reduced-order models from input/output data. in 2016 IEEE 55th Conference on Decision and Control, CDC 2016., 7799420, Institute of Electrical and Electronics Engineers Inc., pp. 7453-7458, 55th IEEE Conference on Decision and Control, CDC 2016, Las Vegas, United States, 12/12/16. https://doi.org/10.1109/CDC.2016.7799420
Scarciotti G, Jiang Z-P, Astolfi A. Constrained optimal reduced-order models from input/output data. In 2016 IEEE 55th Conference on Decision and Control, CDC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 7453-7458. 7799420 https://doi.org/10.1109/CDC.2016.7799420
Scarciotti, Giordano ; Jiang, Zhong-Ping ; Astolfi, Alessandro. / Constrained optimal reduced-order models from input/output data. 2016 IEEE 55th Conference on Decision and Control, CDC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 7453-7458
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