Title: Reduced complexity Volterra model of non-linear MISO system

Authors: Abdelkader Mbarek; Tarek Garna; Kais Bouzrara; Hassani Messaoud

Addresses: Laboratory of Automatic Control and Signal Processing, National Engineering School of Monastir, 5000, Monastir, Tunisia. ' Laboratory of Automatic Control and Signal Processing, National Engineering School of Monastir, 5000, Monastir, Tunisia. ' Laboratory of Automatic Control and Signal Processing, National Engineering School of Monastir, 5000, Monastir, Tunisia. ' Laboratory of Automatic Control and Signal Processing, National Engineering School of Monastir, 5000, Monastir, Tunisia

Abstract: In this paper, we propose a new dynamic non-linear MISO system model using discrete-time Volterra series. To provide a reduced complexity model, each Volterra kernel is expanded on independent generalised orthonormal bases (GOBs) associated to the inputs to develop a new black-box non-linear MISO-GOB-Volterra model. However, this reduction is ensured once the poles characterising each independent generalised orthonormal basis (GOB) are set to their optimal values. For the selection of optimal GOBs poles, we develop two new general approaches based on Gauss-Newton and exhaustive algorithms, the performances of which are illustrated and compared in simulation.

Keywords: nonlinear MISO systems; Volterra models; reduced complexity; parametric complexity; generalised orthonormal basis; GOB; optimisation; dynamic modelling; simulation.

DOI: 10.1504/IJMIC.2012.047121

International Journal of Modelling, Identification and Control, 2012 Vol.16 No.2, pp.134 - 148

Published online: 17 Dec 2014 *

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