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System identification application using Hammerstein model

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Abstract

Generally, memoryless polynomial nonlinear model for nonlinear part and finite impulse response (FIR) model or infinite impulse response model for linear part are preferred in Hammerstein models in literature. In this paper, system identification applications of Hammerstein model that is cascade of nonlinear second order volterra and linear FIR model are studied. Recursive least square algorithm is used to identify the proposed Hammerstein model parameters. Furthermore, the results are compared to identify the success of proposed Hammerstein model and different types of models.

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Acknowledgment

This work is supported by Research Fund of Erciyes University (Project code: FDK-2014-5308).

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Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Erciyes University, 38039, Kayseri, Turkey

    Saban Ozer & Hasan Zorlu

  2. Kayseri Regional Office, Turk Telekom A.S., 38070, Kayseri, Turkey

    Selcuk Mete

Authors
  1. Saban Ozer
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  2. Hasan Zorlu
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  3. Selcuk Mete
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Correspondence to Hasan Zorlu.

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Ozer, S., Zorlu, H. & Mete, S. System identification application using Hammerstein model. Sādhanā 41, 597–605 (2016). https://doi.org/10.1007/s12046-016-0505-8

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  • DOI: https://doi.org/10.1007/s12046-016-0505-8

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