2021
DOI: 10.3390/pr9122113
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A Weighted EFOR Algorithm for Dynamic Parametrical Model Identification of the Nonlinear System

Abstract: In this paper, the Nonlinear Auto-Regressive with exogenous inputs (NARX) model with parameters of interest for design (NARX-M-for-D), where the design parameter of the system is connected to the coefficients of the NARX model by a predefined polynomial function is studied. For the NARX-M-for-D of nonlinear systems, in practice, to predict the output by design parameter values are often difficult due to the uncertain relationship between the design parameter and the coefficients of the NARX model. To solve thi… Show more

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Cited by 2 publications
(1 citation statement)
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“…On the other hand, a numerical representation model of the rotor-bearing system can be established based on a data-driven modeling method without any prior knowledge, except for the input and output data sets [15][16][17]. In the past decades, the data-driven modeling method is widely used for constructing the mathematical model to reveal the dynamic characteristics of nonlinear systems [18][19][20][21][22].…”
Section: Introductionmentioning
confidence: 99%
“…On the other hand, a numerical representation model of the rotor-bearing system can be established based on a data-driven modeling method without any prior knowledge, except for the input and output data sets [15][16][17]. In the past decades, the data-driven modeling method is widely used for constructing the mathematical model to reveal the dynamic characteristics of nonlinear systems [18][19][20][21][22].…”
Section: Introductionmentioning
confidence: 99%