Adaptive neuro-fuzzy control of wet scrubbing process

dc.contributor.authorSalami, Momoh-Jimoh E.
dc.contributor.authorDanzomo, Bashir A.
dc.contributor.authorKhan, Raisuddin
dc.date.accessioned2019-10-16T13:55:00Z
dc.date.available2019-10-16T13:55:00Z
dc.date.issued2015-05-31
dc.description.abstractThenon-linear characteristics of wet scrubbing process have led to the application of intelligent control technique to adequately deal with these complexities by manipulating the liquid droplet size for the effective control of particulate matter (PM) contaminants. This includes the use of adaptive neuro-fuzzy inference system (ANFIS) to design an intelligent controller based on direct inverse model control strategy using default input and output membership functions (gaussmf and linear) and different number of input membership functions. This is followed by training of the fuzzy inference system to obtain inverse model which was tested as the intelligent controller. The controller developed using two-input membership functions have successfully achieved the main target of setting the PM concentration (process output) below the set point which is the allowable World health organization (WHO) emission level for 20g/μm within a short settling time of 2s. © 2015 IEEE.en_US
dc.identifier.citationSalami, M. J. E., Danzomo, B. A., & Khan, M. R. (2015, May). Adaptive neuro-fuzzy control of wet scrubbing process. In 2015 10th Asian Control Conference (ASCC) (pp. 1-6). IEEE.en_US
dc.identifier.uri10.1109/ASCC.2015.7244419
dc.identifier.urihttp://repository.elizadeuniversity.edu.ng/handle/20.500.12398/552
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectAdaptive neuro-fuzzy controlen_US
dc.subjectWet scrubber systemen_US
dc.subjectWet scrubbing processen_US
dc.titleAdaptive neuro-fuzzy control of wet scrubbing processen_US
dc.typeArticleen_US
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