Interval Type-2 Fuzzy Neural Network Control for Furnace Temperature in Municipal Solid Waste Incineration Processes - 文章详情页

作者：

Tian, Hao (Tian, Hao.) | Tang, Jian (Tang, Jian.) | Xia, Heng (Xia, Heng.)

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EI Scopus

摘要：

Furnace　temperature　plays　a　pivotal　role　in　ensuring　the　stability　of　municipal　solid　waste　incineration　(MSWI),　influenced　by　variable　factors　such　as　material　composition,　feeding　patterns,　and　equipment　operation.　We　introduce　an　interval　type-2　fuzzy　neural　network　(IT2FNN)　control　method.　Initially,　we　analyze　furnace　temperature　control　characteristics　to　identity　crucial　operating　variables.　Subsequently,　we　construct　a　multiple-input　single-output　(MISO)　model　for　furnace　temperature　using　the　linear　regression　decision　tree　(LRDT)　algorithm.　Finally,　we　develop　an　IT2FNN-based　controller　for　furnace　temperature.　The　effectiveness　of　our　proposed　method　is　confirmed　through　control　experiments　using　actual　MSWI　process　data.　©　2024　IEEE.

关键词：

Furnaces Waste incineration Municipal solid waste Fuzzy inference Fuzzy neural networks Temperature Temperature control Decision trees

作者机构：

[ 1 ] [Tian, Hao]Beijing University Of Technology, Faculty Of Information Technology, Beijing, China
[ 2 ] [Tang, Jian]Beijing University Of Technology, Faculty Of Information Technology, Beijing, China
[ 3 ] [Xia, Heng]Beijing University Of Technology, Faculty Of Information Technology, Beijing, China

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