Computing an initial estimate of a Wiener-Hammerstein system with a random phase multisine excitation

Wiener-Hammerstein systems consist of two linear dynamic systems placed around a static nonlinearity. These models are difficult to identify due to the presence of two dynamic systems. Usually, a nonlinear estimation procedure is necessary to estimate the parameters of the different parts. This nonlinear estimation procedure needs good starting values to converge quickly and/or reliably to a global minimum. This paper proposes a method to compute a first estimate based on one measurement record only.

[1]  Johan Schoukens,et al.  Initial estimates of Wiener and Hammerstein systems using multisine excitation , 2001, IEEE Trans. Instrum. Meas..

[2]  Steve McLaughlin,et al.  Analysis of stochastic gradient identification of Wiener-Hammerstein systems for nonlinearities with Hermite polynomial expansions , 2001, IEEE Trans. Signal Process..

[3]  Johan Schoukens,et al.  Practical choices in the FRF measurement in presence of nonlinear distortions , 1999, IMTC/99. Proceedings of the 16th IEEE Instrumentation and Measurement Technology Conference (Cat. No.99CH36309).

[4]  C. H. Chen,et al.  Maximum likelihood identification of stochastic Weiner-Hammerstein-type non-linear systems , 1992 .

[5]  Johan Schoukens,et al.  Design of multisine excitations to characterize the nonlinear distortions during FRF-measurements , 2001, IEEE Trans. Instrum. Meas..

[6]  Keith R. Godfrey,et al.  Identification of Wiener-Hammerstein models using linear interpolation in the frequency domain (LIFRED) , 2002, IEEE Trans. Instrum. Meas..

[7]  Yves Rolain,et al.  Non-parametric Estimation of the Frequency-response Functions of the Linear Blocks of a Wiener-Hammerstein Model , 1997, Autom..

[8]  Roderick Murray-Smith,et al.  Nonlinear structure identification with application to wiener-hammerstein systems , 2003 .

[9]  Stephen P. Boyd,et al.  Uniqueness of a basic nonlinear structure , 1983 .

[10]  M. Boutayeb,et al.  Recursive identification method for MISO Wiener-Hammerstein model , 1995, IEEE Trans. Autom. Control..

[11]  Keith R. Godfrey,et al.  Identification of wiener-hammerstein models with cubic nonlinearity using lifred , 2003 .

[12]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .