multiple-input single-output nonlinear system identification using bezier- bernstein polynomials with noise cancellation

This article deals with an identification method for the fractional multiple-input single-output ‎model. it is considered the hammerstein model to separate dynamic linear and static nonlinear ‎behaviors. which bezier-bernstein polynomials are used to approximate the nonlinear functions ‎and the fractional order transfer function is applied to estimate the linear part. a hybrid ‎identification method based on a modified evolutionary algorithm and a recursive classic method ‎is presented. as an advantage, this method can also correctly identify the system in the presence ‎of output noise. a photovoltaic experimental system and a numerical example are used to ‎illustrate the efficiency and performance of the proposed scheme.‎