“Dynamic Relative Gain Array Estimation using Local Polynomial Approximation Approach”

Authors: Ali M. H. Kadhim, Wolfgang Birk and Miguel Castano Arranz,
Affiliation: Luleå University of Technology
Reference: 2016, Vol 37, No 4, pp. 247-259.

Keywords: Dynamic Relative Gain Array, nonparametric identification, local polynomial approximation approach, weakly nonlinear systems

Abstract: This article presents a procedure that utilizes the local polynomial approximation approach in the estimation of the Dynamic Relative Gain Array (DRGA) matrix and its uncertainty bounds for weakly nonlinear systems. This procedure offers enhanced frequency resolution and noise reduction when random excitation is used. It also allows separation of nonlinear distortions with shorter measuring time when multisine excitation is imposed. The procedure is illustrated using the well-known quadruple tank process as a case study in simulation and in real life. Besides, a comparison with the pairing results of the static RGA, nonlinear RGA and DRGA based on linearized quadruple tank model for different simulation cases is performed.

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DOI forward links to this article:
[1] Miguel Castano Arranz and Wolfgang Birk (2017), doi:10.1109/MED.2017.7984309
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[7] Neha Belwal and Pradeep Kumar Juneja (2024), doi:10.1109/ICIC3S61846.2024.10603288
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BibTeX:
@article{MIC-2016-4-5,
  title={{Dynamic Relative Gain Array Estimation using Local Polynomial Approximation Approach}},
  author={Kadhim, Ali M. H. and Birk, Wolfgang and Arranz, Miguel Castano},
  journal={Modeling, Identification and Control},
  volume={37},
  number={4},
  pages={247--259},
  year={2016},
  doi={10.4173/mic.2016.4.5},
  publisher={Norwegian Society of Automatic Control}
};