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<p>The non-Gaussian characteristic of the external disturbance poses a great challenge for system modeling and identification. This paper develops a robust recursive estimation algorithm for the errors-in-variables nonlinear system with the impulsive noise. The algorithm is formulated by minimizing the continuous logarithmic mixed p-norm criterion, and is capable of giving a robust estimation against the impulsive noise through an adjustable weight gain. The nonlinear monomials of the noisy input are estimated by the recursive expressions based on the bias correction. Furthermore, a continuous logarithmic mixed p-norm based robust hierarchical estimation algorithm is derived to reduce the computational loads. The simulation studies demonstrate the feasibility of the proposed algorithms.</p>

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Robust recursive estimation for the errors-in-variables nonlinear systems with impulsive noise

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月19日

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  • Xuehai Wang,
  • Fang Zhu

摘要

The non-Gaussian characteristic of the external disturbance poses a great challenge for system modeling and identification. This paper develops a robust recursive estimation algorithm for the errors-in-variables nonlinear system with the impulsive noise. The algorithm is formulated by minimizing the continuous logarithmic mixed p-norm criterion, and is capable of giving a robust estimation against the impulsive noise through an adjustable weight gain. The nonlinear monomials of the noisy input are estimated by the recursive expressions based on the bias correction. Furthermore, a continuous logarithmic mixed p-norm based robust hierarchical estimation algorithm is derived to reduce the computational loads. The simulation studies demonstrate the feasibility of the proposed algorithms.