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primary topic: Nonlinear system identification via basis functions based time domain volterra model

Nonlinear system identification via basis functions based time domain volterra model
type: AcademicArticle
type: Article
abstract: This paper proposes basis functions based time domain Volterra model for nonlinear system identification. The Volterra kernels are expanded by using complex exponential basis functions and estimated via genetic algorithm (GA). The accuracy and practicability of the proposed method are then assessed experimentally from a scaled 1:100 model of a prototype truss spar platform. Identification results in time and frequency domain are presented and coherent functions are performed to check the quality of the identification results. It is shown that results between experimental data and proposed method are in good agreement. © 2014 Owned by the authors, published by EDP Sciences.
date: 2014
volume: 13
is part of: MATEC Web of Conferences
status: peerReviewed
status: published
author list: authors
type: EPrint
type: ConferenceItemEPrint
is part of: repository

EDP Sciences
type: Organization

MATEC Web of Conferences
type: Collection
issn: 2261236X

C.Y. Ng
type: Person
given name: C.Y.
family name: Ng

E. Yazid
type: Person
given name: E.
family name: Yazid

V.J. Kurian
type: Person
given name: V.J.
family name: Kurian

M.S. Liew
type: Person
given name: M.S.
family name: Liew

S. Parman
type: Person
given name: S.
family name: Parman

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primary topic: Nonlinear system identification via basis functions based time domain volterra model