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Decomposition Least-Squares-Based Iterative Identification Algorithms for Multivariable Equation-Error Autoregressive Moving Average Systems

Author

Listed:
  • Lijuan Wan

    (College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266061, China)

  • Ximei Liu

    (College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266061, China)

  • Feng Ding

    (School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China
    Department of Mathematics, King Abdulaziz University, Jeddah 21589, Arabia)

  • Chunping Chen

    (Editorial Office of Journal of Qingdao University of Science and Technology (Natural Science Edition), Qingdao University of Science and Technology, Qingdao 266061, China)

Abstract

This paper is concerned with the identification problem for multivariable equation-error systems whose disturbance is an autoregressive moving average process. By means of the hierarchical identification principle and the iterative search, a hierarchical least-squares-based iterative (HLSI) identification algorithm is derived and a least-squares-based iterative (LSI) identification algorithm is given for comparison. Furthermore, a hierarchical multi-innovation least-squares-based iterative (HMILSI) identification algorithm is proposed using the multi-innovation theory. Compared with the LSI algorithm, the HLSI algorithm has smaller computational burden and can give more accurate parameter estimates and the HMILSI algorithm can track time-varying parameters. Finally, a simulation example is provided to verify the effectiveness of the proposed algorithms.

Suggested Citation

  • Lijuan Wan & Ximei Liu & Feng Ding & Chunping Chen, 2019. "Decomposition Least-Squares-Based Iterative Identification Algorithms for Multivariable Equation-Error Autoregressive Moving Average Systems," Mathematics, MDPI, vol. 7(7), pages 1-20, July.
    • Handle: RePEc:gam:jmathe:v:7:y:2019:i:7:p:609-:d:246742
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    References listed on IDEAS

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