Model order reduction of LPV systems based on parameter varying modal decomposition

Istvan Gozse, Tamas Luspay, Tamas Peni, Zoltan Szabo, Balint Vanek

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

7 Citations (Scopus)

Abstract

The model reduction problem of high dimensional Linear Parameter Varying (LPV) systems is addressed in the paper. Modal representation of local systems is computed first for fixed values of the scheduling parameter. Modes are then matched and a smooth quasi-modal form is obtained over the entire parameter domain. Classification of system modes is applied to explore dynamic coherence of the model. Structured parameter-varying Gramians are constructed and used for balancing the model and eliminating negligible components. Numerical example illustrates the effectiveness of the methodology.

Original languageEnglish
Title of host publication2016 IEEE 55th Conference on Decision and Control, CDC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7459-7464
Number of pages6
ISBN (Electronic)9781509018376
DOIs
Publication statusPublished - Dec 27 2016
Event55th IEEE Conference on Decision and Control, CDC 2016 - Las Vegas, United States
Duration: Dec 12 2016Dec 14 2016

Publication series

Name2016 IEEE 55th Conference on Decision and Control, CDC 2016

Other

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

ASJC Scopus subject areas

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

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  • Cite this

    Gozse, I., Luspay, T., Peni, T., Szabo, Z., & Vanek, B. (2016). Model order reduction of LPV systems based on parameter varying modal decomposition. In 2016 IEEE 55th Conference on Decision and Control, CDC 2016 (pp. 7459-7464). [7799421] (2016 IEEE 55th Conference on Decision and Control, CDC 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2016.7799421