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

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Zolfagharian, Ali, Noshadi, Amin, Md Zain, Mohd Zarhamdy and Abu-Bakar, Ariza Sharikin (2012) Practical multi-objective controller for preventing noise and vibration in an automobile wiper system. Swarm and Evolutionary Computation, 8. pp. 54-68. ISSN 2210-6502

Abstract

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.

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/23396
DOI https://doi.org/10.1016/j.swevo.2012.08.004
Official URL http://www.sciencedirect.com/science/article/pii/S...
Subjects Historical > FOR Classification > 0913 Mechanical Engineering
Current > Division/Research > College of Science and Engineering
Keywords ResPubID25558, ResPubID26687, automotive wiper, noise and vibration, non-linear system identification, input shaping, iterative learning, multi objective genetic algorithm
Citations in Scopus 15 - View on Scopus
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