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dc.contributor.authorAbbaspour, Alireza
dc.contributor.authorKhalilnejad, Arash
dc.contributor.authorChen, Zheng
dc.date.accessioned2017-01-06T23:56:05Z
dc.date.available2017-01-06T23:56:05Z
dc.date.issued2016-11-26
dc.identifier.citationAbbaspour, Alireza; Khalilnejad, Arash; Chen, Zheng. 2016. Robust adaptive neural network control for PEM fuel cell. International Journal of Hydrogen Energy, vol. 41:no. 44, 26 November 2016:pp 20385–20395en_US
dc.identifier.issn0360-3199
dc.identifier.otherWOS:000387521900049
dc.identifier.urihttp://dx.doi.org/10.1016/j.ijhydene.2016.09.075
dc.identifier.urihttp://hdl.handle.net/10057/12785
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractThis paper presents a robust neural network adaptive control for polymer electrolyte membrane (PEM) fuel cells (FCs). Since deviations between the partial pressure of hydrogen and oxygen in PEMFCs lead to serious membrane damage, it is desirable to have a robust and adaptive control to stabilize the partial pressure, which can significantly lengthen their lifetime. Due to inherent nonlinearities in PEMFC dynamics and variations of the system parameters, a linear control with fixed gains cannot control the PEMFC system properly. Therefore, a neural network adaptive control with feedback linearization is developed for this system. With a feedback linearization control only, the performance is deviated in the presence of unknown dynamics and disturbances. Thus, a robust adaptive neural network control is added to the feedback linearization control to reduce the deviation. Simulation results show that the proposed control can significantly enhance the output performance as well as reject the disturbances.en_US
dc.description.sponsorshipNational Science Foundation under the Award No. EPS-0903806 and matching support from the State of Kansas through the Kansas Board of Regents.en_US
dc.language.isoen_USen_US
dc.publisherElsevier Ltd. All rights reserved.en_US
dc.relation.ispartofseriesInternational Journal of Hydrogen Energy;v.41:no.44
dc.subjectAdaptive controlen_US
dc.subjectPEMFCen_US
dc.subjectNonlinear dynamicen_US
dc.subjectNeural networken_US
dc.subjectRobustnessen_US
dc.titleRobust adaptive neural network control for PEM fuel cellen_US
dc.typeArticleen_US
dc.rights.holder(C) 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.en_US


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