Identification of decoupled polynomial narx model using simulation error minimization

Kiana Karami, David Westwick, Johan Schoukens

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

Samenvatting

The Polynomial Nonlinear Auto-Regressive eXogenous input (P-NARX) model, a multivariable polynomial of past input and output values, is a widely used equation error nonlinear system model. The number of model parameters grows rapidly with the polynomial degree, and with the number of past inputs and outputs, but can be reduced significantly by adopting a decoupled structure, consisting of a transformation matrix followed by a bank of single-input single-output polynomials whose outputs are summed to produce the final output. Prediction Error Minimization (PEM) is a classical approach for the identification of both linear and nonlinear systems. Models trained using PEM may not be suitable for system simulation, where the model only has access to the system's inputs. In this paper, an identification method based on Simulation Error Minimization (SEM) for Decoupled P-NARX models is proposed. The proposed algorithm is applied to data from two nonlinear system identification benchmarks and the performance is compared to a previous PEM based algorithm.

Originele taal-2Engels
Titel2019 American Control Conference, ACC 2019
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's4362-4367
Aantal pagina's6
ISBN van elektronische versie978-1-5386-7926-5
StatusGepubliceerd - 1 jul 2019
Evenement2019 American Control Conference, ACC 2019 - Philadelphia, Verenigde Staten van Amerika
Duur: 10 jul 201912 jul 2019
http://acc2019.a2c2.org

Congres

Congres2019 American Control Conference, ACC 2019
Verkorte titelACC2019
LandVerenigde Staten van Amerika
StadPhiladelphia
Periode10/07/1912/07/19
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  • Citeer dit

    Karami, K., Westwick, D., & Schoukens, J. (2019). Identification of decoupled polynomial narx model using simulation error minimization. In 2019 American Control Conference, ACC 2019 (blz. 4362-4367). [8815172] Piscataway: Institute of Electrical and Electronics Engineers.