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Abstract:
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 identify 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.
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Source :
PROCEEDINGS OF THE 36TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC 2024
ISSN: 1948-9439
Year: 2024
Page: 1706-1709
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SCOPUS Cited Count:
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 7
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