Identification of Hammerstein-Wiener Systems Including Backlash Input Nonlinearities
نویسندگان
چکیده
Standard Hammerstein-Wiener models consist of a linear subsystem sandwiched by two memoryless nonlinearities. Presently, the input nonlinearity is allowed to be a memory operator of backlash type and both input and output nonlinearities are polynomial and may be noninvertible. The linear subsystem may be parametric or not, continuousor discrete-time. A two-stage identification method is developed such the parameters of all nonlinear elements are estimated first using the KozenLandau polynomial decomposition algorithm. The obtained estimates are then based upon in the identification of the linear subsystem, making use of suitable pread post-compensators.
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