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Time-delay Hammerstein system identification using modified cross-correlation method and variable stacking length multi-error algorithm

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  • Jing, Shaoxue

Abstract

In this paper, the identification of a time delay Hammerstein system is considered. Based on a normalized Gaussian white input, a cross-correlation function increment method is investigated to estimate the time delay without the parameter estimates. The integer delay is obtained directly, not by rounding a decimal delay estimate. To identify the parameters, a novel multi-error information gradient algorithm with variable stacking length is proposed. In the parameter identification algorithm, the slow stochastic information gradient algorithm is accelerated by a stacked error named multi-error and the variable stacking length is determined by a loss function descent criterion. Several simulation experiments validate the proposed algorithm.

Suggested Citation

  • Jing, Shaoxue, 2023. "Time-delay Hammerstein system identification using modified cross-correlation method and variable stacking length multi-error algorithm," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 207(C), pages 288-300.
    • Handle: RePEc:eee:matcom:v:207:y:2023:i:c:p:288-300
    DOI: 10.1016/j.matcom.2022.12.031
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    References listed on IDEAS

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    1. Ling Xu & Feng Ding & Quanmin Zhu, 2021. "Decomposition strategy-based hierarchical least mean square algorithm for control systems from the impulse responses," International Journal of Systems Science, Taylor & Francis Journals, vol. 52(9), pages 1806-1821, July.
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    4. Wei, Yun & Tian, Qing & Guo, Jianhua & Huang, Wei & Cao, Jinde, 2019. "Multi-vehicle detection algorithm through combining Harr and HOG features," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 155(C), pages 130-145.
    5. Abubakar, Auwal Bala & Kumam, Poom & Malik, Maulana & Ibrahim, Abdulkarim Hassan, 2022. "A hybrid conjugate gradient based approach for solving unconstrained optimization and motion control problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 201(C), pages 640-657.
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