Practical multi-objective controller for preventing noise and vibration in an automobile wiper system
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journal contribution
posted on 2013-02-01, 00:00 authored by Ali ZolfagharianAli Zolfagharian, A Noshadi, M Z M Zain, A R A BakarThis 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 computationVolume
8Pagination
54 - 68Publisher
ElsevierLocation
Amsterdam, The NetherlandsPublisher DOI
ISSN
2210-6502Language
engPublication classification
C1.1 Refereed article in a scholarly journalCopyright notice
2012, Elsevier B.V.Usage metrics
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Keywords
Science & TechnologyTechnologyComputer Science, Artificial IntelligenceComputer Science, Theory & MethodsComputer ScienceAutomotive wiperNoise and vibrationNon-linear system identificationInput shapingIterative learningMulti objective genetic algorithmLINK FLEXIBLE MANIPULATOROPTIMIZATIONSELECTIONArtificial Intelligence and Image ProcessingComputation Theory and Mathematics
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