Nonlinear dynamic modeling of fuel cell systems using wavelet network-based Hammerstein models

Wei Wu, Hsiao Tung Yang, Da Wei Jhao

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

A control-oriented multivariable Hammerstein model is used to identify the strongly nonlinear dynamics of fuel cell systems that are described by nonlinear differential or differential-algebraic equations. Within the Hammerstein model framework, the static nonlinear part is constructed by a wavelet network, and the linear dynamic part is described by a discrete-time transfer function of the state-space model. For prescribed input-output patterns for high-order fuel cell systems, simulations demonstrate the accuracy of system identification using wavelet networks in the Hammerstein structure that is better than that in the neural network structure.

Original languageEnglish
Pages (from-to)625-630
Number of pages6
JournalJOURNAL of CHEMICAL ENGINEERING of JAPAN
Volume46
Issue number9
DOIs
Publication statusPublished - 2013 Sep 25

All Science Journal Classification (ASJC) codes

  • Chemical Engineering(all)
  • Chemistry(all)

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