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Proceedings of the IEEE

Issue 3 • Mar 1995

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Displaying Results 1 - 7 of 7
  • Fuzzy logic control-a taxonomy of demonstrated benefits

    Publication Year: 1995, Page(s):407 - 421
    Cited by:  Papers (29)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1452 KB)

    The motivations for fuzzy logic control (FLC) are illuminated by exploring the benefits obtained by application designers through its use. A context for this exploration is set with a discussion of the characteristics of control policies and of the general attributes of FLC. Each benefit is described by reference to reported FLC implementations in which the benefit is demonstrated. Based on common... View full abstract»

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  • Neuro-fuzzy modeling and control

    Publication Year: 1995, Page(s):378 - 406
    Cited by:  Papers (385)  |  Patents (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2292 KB)

    Fundamental and advanced developments in neuro-fuzzy synergisms for modeling and control are reviewed. The essential part of neuro-fuzzy synergisms comes from a common framework called adaptive networks, which unifies both neural networks and fuzzy models. The fuzzy models under the framework of adaptive networks is called adaptive-network-based fuzzy inference system (ANFIS), which possess certai... View full abstract»

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  • Industrial applications of fuzzy logic at General Electric

    Publication Year: 1995, Page(s):450 - 465
    Cited by:  Papers (55)  |  Patents (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1404 KB)

    Fuzzy logic control (FLC) technology has drastically reduced the development time and deployment cost for the synthesis of nonlinear controllers for dynamic systems. As a result we have experienced an increased number of FLC applications. We illustrate some of our efforts in FLC technology transfer, covering projects in turboshaft aircraft engine control, steam turbine startup, steam turbine cycli... View full abstract»

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  • Fuzzy logic systems for engineering: a tutorial

    Publication Year: 1995, Page(s):345 - 377
    Cited by:  Papers (761)  |  Patents (26)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2824 KB)

    A fuzzy logic system (FLS) is unique in that it is able to simultaneously handle numerical data and linguistic knowledge. It is a nonlinear mapping of an input data (feature) vector into a scalar output, i.e., it maps numbers into numbers. Fuzzy set theory and fuzzy logic establish the specifics of the nonlinear mapping. This tutorial paper provides a guided tour through those aspects of fuzzy set... View full abstract»

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  • Application of fuzzy logic to reliability engineering

    Publication Year: 1995, Page(s):435 - 449
    Cited by:  Papers (57)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1112 KB)

    The analysis of system reliability often requires the use of subjective-judgments, uncertain data, and approximate system models. By allowing imprecision and approximate analysis fuzzy logic provides an effective tool for characterizing system reliability in these circumstances; it does not force precision where it is not possible. Here we apply the main concepts of fuzzy logic, fuzzy arithmetic a... View full abstract»

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  • Hardware solutions for fuzzy control

    Publication Year: 1995, Page(s):422 - 434
    Cited by:  Papers (53)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1080 KB)

    A large fraction of software designs using microcontrollers is today adopting fuzzy logic algorithms and this fraction is likely to increase in the future. Hardware implementation of fuzzy logic ranges from standard microprocessors to dedicated ASICs and each different approach is targeted to a different application domain or market area. In this paper, we present an overview of the computational ... View full abstract»

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  • Expert supervision of fuzzy learning systems for fault tolerant aircraft control

    Publication Year: 1995, Page(s):466 - 483
    Cited by:  Papers (38)  |  Patents (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1592 KB)

    In this paper, we begin by showing that the fuzzy model reference learning controller (FMRLC) can be used to reconfigure the nominal controller in an F-16 aircraft to compensate for various actuator failures without using explicit failure information. Next, we show that the performance of the FMRLC can be significantly enhanced by exploiting failure detection and identification (FDI) information t... View full abstract»

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North Carolina State University