Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/132881
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dc.titleFuzzy logic control of batch-feeding refuse incineration
dc.contributor.authorChen, Desong
dc.date.accessioned2016-12-13T05:37:38Z
dc.date.available2016-12-13T05:37:38Z
dc.date.issued1995
dc.identifier.citationChen, Desong (1995). Fuzzy logic control of batch-feeding refuse incineration. Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS : 58-63. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/132881
dc.description.abstractMunicipal Solid Waste (MSW) or refuse incineration plant is designated to reduce the volume of the refuse and recover the energy from it. The steam generated from a boiler heated by burning refuse is sent to a turbine to generate the electricity. Batch-feeding style and the uncertainty of refuse composites result in periodical and uncertain fluctuation of refuse combustion and then the steam flow rate. The fluctuation could lead to the unsteady generation of the electricity. Moreover, the incomplete combustion of the refuse is often observed. This leads to the poor efficiency of refuse volume reduction and the energy recovery. Therefore, the proper controlled combustion of the refuse will be of both environmental and commercial significance. In this paper, we explore the problems of refuse combustion control and discuss how rule-base fuzzy logic control algorithms can be used to damp the fluctuation of the steam flow rate and achieve more complete combustion of the refuse by properly adjusting the grate rotating rates. The extensive simulations based on the data and information from the Ulu Pandan refuse incineration plant, Singapore, show the effectiveness of the rule-base fuzzy logic controller and indicate that the proposed control algorithm has potential of about 10% increase on the capacity of refuse processing and electricity generation.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentELECTRICAL ENGINEERING
dc.description.sourcetitleAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS
dc.description.page58-63
dc.identifier.isiutNOT_IN_WOS
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