A comparative Study of Model-Based and Data-Based Model Order Reduction Techniques for Nonlinear Systems

T. Aizad, Othman Maganga, Malgorzata Sumislawska, Keith J. Burnham

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In this paper a comparative study of three nonlinear model order reduction techniques using a case study of a transmission line model is presented. The investigated model order reduction techniques are: quadratic approximation, trajectory piecewise linear approximation and data-based identification of bilinear model. The performance of model order reduction techniques has been evaluated in terms of their accuracy and computational cost. The original 100th order nonlinear model is reduced to 12th and 20th order models by using three different MOR techniques yet preserving simulation accuracy
Original languageEnglish
Title of host publicationAdvances in Intelligent Systems and Computing: Proceedings of the Twenty-Third International Conference on Systems Engineering
EditorsHenry Selvaraj, Dawid Zydek, Grzegorz Chmaj
PublisherSpringer Verlag
Pages83-88
Volume1089
ISBN (Print)978-3-319-08421-3
DOIs
Publication statusPublished - 2015

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Bibliographical note

This paper is not available on the repository. The paper was given at the 23rd International Conference on Systems Engineering, ICSEng 2014; Las Vegas, NV; United States; 19 August 2014 through 21 August 2014

Keywords

  • Computer simulation
  • Piecewise linear techniques
  • Systems engineering
  • Transmission line theory
  • Comparative studies
  • Computational costs
  • Data-based modeling
  • Model order reduction
  • Piecewise linear approximations
  • Quadratic approximation
  • Simulation accuracy
  • Transmission line modeling

Cite this

Aizad, T., Maganga, O., Sumislawska, M., & Burnham, K. J. (2015). A comparative Study of Model-Based and Data-Based Model Order Reduction Techniques for Nonlinear Systems. In H. Selvaraj, D. Zydek, & G. Chmaj (Eds.), Advances in Intelligent Systems and Computing: Proceedings of the Twenty-Third International Conference on Systems Engineering (Vol. 1089, pp. 83-88). Springer Verlag. https://doi.org/10.1007/978-3-319-08422-0_12