Title
Parameter identification of Hammerstein systems with Bouc-Wen hysteresis input nonlinearity*
Abstract
The problem of Hammerstein system identification is addressed in presence of a differential hysteresis nonlinearity. The identification process is based on sampled output measurements and an upper bound on the allowed sampling period is provided. One key idea in the identification method design is that the hysteresis element assumes a linear parameterization in presence of a specific class of periodic excitations. Then, a linearly parameterized representation, involving a set of lumped parameters, can be associated to the whole Hammerstein system. The consistent estimation of these lumped parameters is shown to be possible using a hybrid adaptive observer. Finally, the recovery of the true system parameters is achieved using several tools including matrix SVD and nonlinear least-squares estimators.
Year
DOI
Venue
2014
10.1109/ECC.2014.6862340
ECC
Keywords
Field
DocType
least squares approximations,observers,parameter estimation,sampling methods,singular value decomposition,bouc-wen hysteresis input nonlinearity,hammerstein system identification,differential hysteresis nonlinearity,hybrid adaptive observer,identification method design,linear parameterization,linearly parameterized representation,matrix svd,nonlinear least-squares estimators,parameter identification,periodic excitations,sampled output measurements,sampling period
Nonlinear system,Control theory,Hammerstein systems,Hysteresis,Mathematics
Conference
Citations 
PageRank 
References 
0
0.34
8
Authors
3
Name
Order
Citations
PageRank
Abdelhadi Radouane1132.28
Ahmed-Ali, T.200.34
F. Giri311029.41