TY - JOUR
T1 - Nonlinear dynamic modeling of fuel cell systems using wavelet network-based Hammerstein models
AU - Wu, Wei
AU - Yang, Hsiao Tung
AU - Jhao, Da Wei
PY - 2013/9/25
Y1 - 2013/9/25
N2 - 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.
AB - 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.
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U2 - 10.1252/jcej.13we039
DO - 10.1252/jcej.13we039
M3 - Article
AN - SCOPUS:84884392999
VL - 46
SP - 625
EP - 630
JO - Journal of Chemical Engineering of Japan
JF - Journal of Chemical Engineering of Japan
SN - 0021-9592
IS - 9
ER -