Control of a direct internal reforming molten carbonate fuel cell system using wavelet network-based Hammerstein models

Wei Wu, Da Wei Jhao

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Inspired by a direct internal reforming molten carbonate fuel cell (DIR-MCFC) coupled with complicated nonlinear dynamics, the identification and control design of the Hammerstein model is presented. Through the sequential identification procedure, the static nonlinearity block is considered as the wavelet network which is trained and validated by the on-line learning algorithm, and the linear dynamic block is described by the state-space model in which parameters are estimated by the recursive least square algorithm. Using the numerical interpolation technique to approximate the implicit nonlinear function, we present a composite control framework consists of a nonlinear inversion and linear control. Through the closed-loop simulation tests, the nonlinear inversion design for the nonlinearity cancellation of a class of nonlinear systems is validated.

Original languageEnglish
Pages (from-to)653-658
Number of pages6
JournalJournal of Process Control
Volume22
Issue number3
DOIs
Publication statusPublished - 2012 Mar 1

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Hammerstein Model
Wavelet Network
Molten carbonate fuel cells (MCFC)
Fuel Cell
Reforming reactions
Inversion
Control nonlinearities
Nonlinearity
Internal
Implicit Function
Linear Control
Least Square Algorithm
Identification (control systems)
Recursive Algorithm
State-space Model
Cancellation
Nonlinear Function
Control Design
Nonlinear Dynamics
Closed-loop

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Modelling and Simulation
  • Computer Science Applications

Cite this

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Control of a direct internal reforming molten carbonate fuel cell system using wavelet network-based Hammerstein models. / Wu, Wei; Jhao, Da Wei.

In: Journal of Process Control, Vol. 22, No. 3, 01.03.2012, p. 653-658.

Research output: Contribution to journalArticle

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