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Practical multi-objective controller for preventing noise and vibration in an automobile wiper system

Version 2 2024-06-04, 11:38
Version 1 2019-02-18, 13:46
journal contribution
posted on 2024-06-04, 11:38 authored by Ali ZolfagharianAli Zolfagharian, A Noshadi, MZM Zain, ARA Bakar
This paper presents an approach using a multi-objective controller to prevent noise and vibration generated by the wiper blade during its wiping operation. Firstly, this paper focuses on the experimental approach to collect noise and vibration data from a car wiper system during its operation and secondly, to develop black box model of the wiper system using nonparametric approach of system identification known as nonlinear auto regressive exogenous Elman neural network (NARXENN). Finally, a novel closed loop iterative input shaping controller whose parameters are tuned simultaneously by a Pareto based multi objective genetic algorithm (MOGA) are proposed and simulated in such a way that it can prevent unwanted noise and vibration in the wiper system. The main contribution of this work rather the previous studies of automobile wiper system is to develop a novel multi-objective control strategy whereby an automobile wiper blade is moved within its sweep workspace in the least amount of time with minimum noise and vibration. © 2012 Elsevier B.V.

History

Journal

Swarm and evolutionary computation

Volume

8

Pagination

54-68

Location

Amsterdam, The Netherlands

ISSN

2210-6502

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal

Copyright notice

2012, Elsevier B.V.

Publisher

Elsevier

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