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Author:

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

Indexed by:

CPCI-S EI Scopus

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.

Keyword:

interval type-2 fuzzy neural network (IT2FNN) control furnace temperature model Municipal solid waste incineration (MSWI) data-driven

Author Community:

  • [ 1 ] [Tian, Hao]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
  • [ 2 ] [Tang, Jian]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
  • [ 3 ] [Xia, Heng]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China

Reprint Author's Address:

  • [Tian, Hao]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China

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Source :

PROCEEDINGS OF THE 36TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC 2024

ISSN: 1948-9439

Year: 2024

Page: 1706-1709

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 7

Affiliated Colleges:

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