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Fuzzy logic application in automation control

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dc.title Fuzzy logic application in automation control en
dc.contributor.author Nchena, Linos Mabvuto
dc.relation.ispartof 2020 10th International Conference on Advanced Computer Information Technologies (ACIT)
dc.identifier.isbn 978-1-72816-760-2
dc.date.issued 2020
dc.citation.spage 282
dc.citation.epage 287
dc.event.title 10th International Conference on Advanced Computer Information Technologies (ACIT)
dc.event.location Deggendorf
utb.event.state-en Germany
utb.event.state-cs Německo
dc.event.sdate 2020-09-16
dc.event.edate 2020-09-18
dc.type conferenceObject
dc.language.iso en
dc.publisher IEEE
dc.identifier.doi 10.1109/ACIT49673.2020.9208862
dc.relation.uri https://ieeexplore.ieee.org/document/9208862
dc.subject fuzzy logic controller en
dc.subject Newton law of motion en
dc.subject mathematical model en
dc.subject artificial Intelligence en
dc.subject specialized computers en
dc.description.abstract This paper aims to investigate and apply Artificial Intelligence in solving a real-life problem. A fuzzy logic control (FLC) system is proposed for controlling and maintaining speed of a motor vehicle. The vehicle controller produces either a throttle force or brake force. This force is then feed into the vehicle's engine to generate an appropriate acceleration for the vehicle. Moreover, the vehicles' speed is further affected by the type of road the vehicles is moving on. Moving on an uphill road would require more throttle while moving downhill roads require less throttle and more brakes. A flat smooth road requires average throttle or brakes. To evaluate and validate the proposed solution, two models are used, and results are later analyzed. First model uses FLC while second model uses Proportional Integrator (PI) controller. The PI controller has proved to be less smooth in transitioning the actual to desired speed than the FLC. The FLC was further tested on its independence from the model used. It has been assigned to two different models to show that results obtained are based on fuzzy-rules and not the specific model. This experiment successfully demonstrated how motor vehicle speed can be better controlled by using a FLC than a PI controller system en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1010157
utb.identifier.obdid 43883647
utb.identifier.scopus 2-s2.0-85094109849
utb.identifier.wok 000593848900062
utb.source B-wok
dc.date.accessioned 2021-01-08T14:02:35Z
dc.date.available 2021-01-08T14:02:35Z
utb.contributor.internalauthor Nchena, Linos Mabvuto
utb.fulltext.affiliation Linos Nchena Faculty of Applied Informatics Tomas Bata University in Zlín Zlin, Czech Republic nchena@utb.cz
utb.fulltext.dates -
utb.wos.affiliation [Nchena, Linos] Tomas Bata Univ Zlin, Fac Appl Informat, Zlin, Czech Republic
utb.fulltext.faculty Faculty of Applied Informatics
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