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    Please use this identifier to cite or link to this item: https://ir.fy.edu.tw:8080/ir/handle/987654321/10026

    Title: GA-based fuzzy neural controller design for municipal incinerators
    Authors: Chen,W.C.;Chang,Ni-Bin;Chen, Jeng-Chung
    Contributors: 輔英科技大學 環境工程與科學系
    Keywords: Fuzzy sets;Neural network;Genetic algorithm;Control
    Date: 2002-08
    Issue Date: 2010-11-16 16:30:23 (UTC+8)
    Abstract: The successful operation of mass burn municipal incinerators for solid waste management involves many uncertain factors. Not only the physical composition and chemical property of waste streams but also the complexity of combustion mechanism would significantly influence the performance of waste incineration. Due to the rising concerns of dioxin/furan emissions from those incineration facilities in the metropolitan region, the applications of fuzzy control technologies for reducing the operational risks have gradually received wide attention in the scientific community. Recent advances of intelligent combustion control (ICC) technologies indicate that hybrid fuzzy control schemes, integrating some ideas and paradigms existing in different soft computing approaches, may provide more reliable control performance of combustion process. The proposed integrated methodology, using genetic algorithms and neural networks as tools to aid in fuzzy logic control, therefore employs a three-stage analysis. It applies three soft computing approaches simultaneously for generating a representative state function, searching for a set of multi-objective control strategies, and auto-tuning the fuzzy control rule base for use in the case study. The findings from this research clearly indicate that the control performance at least in three types of municipal incinerators (i.e., patented stokers are Takuma, Volund, and Martin) is greatly enhanced via the use of ICC technologies. By using this integrated methodology, the case study not only verifies the applicability and suitability for controlling municipal incinerators but also presents application potentials for controlling many other types of industrial incinerators, such as modular, rotary kiln, and fluidized bed incinerators.
    Relation: Fuzzy Sets and Systems,Volume 129 Issue 3,p.343-369
    Appears in Collections:[環境工程與科學系] 期刊論文

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