Identification of MISO Wiener systems using the LMI algorithm
by Lincheng Zhou; Xiangli Li
International Journal of Modelling, Identification and Control (IJMIC), Vol. 37, No. 3/4, 2021

Abstract: This paper focuses on a new identification method for multiple-input single output (MISO) Wiener nonlinear systems, in which the static nonlinear block is assumed to be a polynomial. The basic idea is to establish a MISO Wiener nonlinear identification model with polynomial nonlinearities by means of the key term separation principle. Then, a new identification method based on Levenberg-Marquardt iterative (LMI) search techniques, which can make full use of all the measured input and output data, but also automatically change the search step-size according to the change values of the quadratic criterion function, is derived to obtain an accurate and fast parameter estimation of the model. Finally, the simulation results demonstrate the efficacy of this method.

Online publication date: Thu, 07-Apr-2022

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