Frequency identification of Hammerstein-Wiener systems with backlash input nonlinearity

The problem of system identification is addressed for Hammerstein-Wiener systems that involve memory operator of backlash type bordered by straight lines as input nonlinearity. The system identification of this model is investigated by using easily generated excitation signals. Moreover, the prior knowledge of the nonlinearity type, being backlash or backlash-inverse, is not required. The nonlinear dynamics and the unknown structure of the linear subsystem lead to a highly nonlinear identification problem. Presently, the output nonlinearity may be noninvertible and the linear subsystem may be nonparametric. Interestingly, the system nonlinearities are identified first using a piecewise constant signal. In turn, the linear subsystem is identified using a frequency approach.