A simulation-free nonlinear model order-reduction approach and comparison study

Behnam Salimbahrami, Boris Lohmann

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

In this paper, a new approach to the model order reduction of nonlinear systems is presented. This approach does not need a simulation of the original system, and therefore, it is suitable for large systems. By separating the linear and nonlinear parts of the original nonlinear model, the idea is to consider the nonlinearities of the resulting system as additional inputs. Based on the linear system from the last step, a known order-reduction method can be applied to find the coefficients of the nonlinear and the linear parts of a reduced-order model. Two different methods from linear-order reduction (balancing and truncation and Eitelberg's method with some modification) are used for this purpose, and their advantages and disadvantages are discussed. For comparison with some known methods in order reduction of nonlinear systems, three other methods are discussed briefly. Finally, a technical nonlinear system is reduced, and different methods are compared.

Original languageEnglish
Pages (from-to)317-329
Number of pages13
JournalMathematical and Computer Modelling of Dynamical Systems
Volume10
Issue number3-4
DOIs
StatePublished - Sep 2004
Externally publishedYes

Keywords

  • Balancing and truncation
  • Eitelberg's method
  • Nonlinear system
  • Order reduction

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