Fuzzy control has emerged as the most important and practical field of study in fuzzy set theory, particularly for industrial developments that do not use conventional control techniques due to the lack of readily available, precise data on input‐output relationships. The foundation of the fuzzy control system is fuzzy logic. Basically, this logical system is considerably more analogous to how people think and speak. A linguistic control approach built on expert knowledge can be transformed into an automatic control strategy using the fuzzy logic–based controller, which is based on the fuzzy logic concept. The understanding of membership functions, in particular, is well‐known and plays a significant role in a variety of applications such as industry, traffic, and medical science. While probability theory deals with randomness, the main objective of fuzzy set theory is to provide a technique for the analysis of uncertainty originating in human subjectivity. The fuzzy logic system focuses primarily on decision‐making and fuzzy inference systems. It includes fuzzification and defuzzification strategies, fuzzy control rules, fuzzy implication, and an analysis of fuzzy reasoning appliances. There are multiple applications of fuzzy logic controls observed in the industrial process. Without the operator having any prior knowledge of the system to be controlled, the industrial controller's hardware aids in fine‐tuning a PID controller. Fuzzy logic supervisory control is utilized in software in the process industry to enhance the functioning of the sintering oven through an advanced integration of priority management and deviation‐controlled timing. It can also be utilized in intelligent control modeling, and programmable logic controller (PLC), where programmed to function in a cost‐effective manner. Additionally, it can be used in a fuzzy image processing scheme, medical engineering vessel segmentation, the development of fuzzy controllers for maintaining an inter‐vehicle safety headway, and knowledge‐based gear‐position decision, among other applications. All these industrial applications are discussed in this chapter.


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    Titel :

    Fuzzy Logic Control for Industrial Applications


    Beteiligte:
    Mondal, Arindam (Herausgeber:in) / Ganguli, Souvik (Herausgeber:in) / Maji, Srabanti (Autor:in) / Ganguli, Souvik (Autor:in)


    Erscheinungsdatum :

    24.06.2025


    Format / Umfang :

    20 pages




    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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