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Dimension reduction for k-power bilinear systems using orthogonal polynomials and Arnoldi algorithm

Author

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  • Zhen-Zhong Qi
  • Yao-Lin Jiang
  • Zhi-Hua Xiao

Abstract

In this paper, a dimension reduction method via general orthogonal polynomials and multiorder Arnoldi algorithm is proposed, which focuses on the topic of structure-preserving for k-power bilinear systems. The main procedure is using a series of expansion coefficient vectors of each state variables in the space spanned by general orthogonal polynomials that satisfy a recurrence formula to generate a projection based on multiorder Arnoldi algorithm. The resulting reduced-order model not only matches a desired number of expansion coefficients of the original output but also retains the topology structure. Meanwhile, the stability is well preserved under some certain conditions and the error bound is also given. Finally, two numerical simulations are provided to illustrate the effectiveness of our proposed algorithm in the views of accuracy and computational cost.

Suggested Citation

  • Zhen-Zhong Qi & Yao-Lin Jiang & Zhi-Hua Xiao, 2021. "Dimension reduction for k-power bilinear systems using orthogonal polynomials and Arnoldi algorithm," International Journal of Systems Science, Taylor & Francis Journals, vol. 52(10), pages 2048-2063, July.
    • Handle: RePEc:taf:tsysxx:v:52:y:2021:i:10:p:2048-2063
    DOI: 10.1080/00207721.2021.1876276
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