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<p>This paper proposes a novel two-stage strategy for identifying three-dimensional resistor-capacitor (3D RC) network models. To bridge the gap between the limited accuracy of conventional integer-order models and the limited practicality of fractional-order models, we introduce an integrated framework that leverages the advantages of both representations. In the first stage, an improved recursive prediction error method is developed to jointly estimate the fractional-order model coefficients and orders, yielding an accurate fractional-order model. In the second stage, this model is converted into an integer-order equivalent via frequency-domain rational approximation and further simplified through balanced truncation to preserve the dominant dynamics while minimizing complexity. Numerical simulations on a 3D RC network validate the effectiveness of the proposed approach, successfully balancing model accuracy with practical utility.</p>

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Two-Stage Identification Strategy for 3D RC Network

  • 期刊论文

  • 发表日期：

    2026年5月29日

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  • Shunyuan Sun,
  • Zhian Xu,
  • Xiao Zhang,
  • Feng Ding

摘要

This paper proposes a novel two-stage strategy for identifying three-dimensional resistor-capacitor (3D RC) network models. To bridge the gap between the limited accuracy of conventional integer-order models and the limited practicality of fractional-order models, we introduce an integrated framework that leverages the advantages of both representations. In the first stage, an improved recursive prediction error method is developed to jointly estimate the fractional-order model coefficients and orders, yielding an accurate fractional-order model. In the second stage, this model is converted into an integer-order equivalent via frequency-domain rational approximation and further simplified through balanced truncation to preserve the dominant dynamics while minimizing complexity. Numerical simulations on a 3D RC network validate the effectiveness of the proposed approach, successfully balancing model accuracy with practical utility.