摘要：AbstractThis paper introduces an iterative algorithm for the identification of time-varying (TV)-Hammerstein systems. This system is composed by a TV static nonlinearity followed by a TV Box-Jenkins linear model. The algorithm uses two basis function expansions: one to represent the TV parameters and a second to approximate the output of the static nonlinearity. A simulation study showed that the algorithm accurately identified the shape of the TV static nonlinearity and linear dynamic elements even though the noise model structure was unknown.
关键词：KeywordsNonlinear Systems IdentificationInstrumental VariableBasis FunctionsPrediction error methods
