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Fuzzy Control of Industrial Systems pp 119–134Cite as

Neurofuzzy Controllers

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Part of the book series: The Springer International Series in Engineering and Computer Science ((SECS,volume 457))

Abstract

Section 5.2 listed three fuzzy system types. The first was the rule-based system where human operator experience is incorporated into a rule set and membership functions. The second (parametric) and third (relational equation based) have reduced the element of human judgment to the construction of membership functions while the rules were generated from measurements.

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Authors and Affiliations

  1. Industrial Electronic Technology Research Group, Rand Afrikaans University, Johannesburg, Republic of South Africa

    Ian S. Shaw

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  1. Ian S. Shaw
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© 1998 Springer Science+Business Media New York

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Shaw, I.S. (1998). Neurofuzzy Controllers. In: Fuzzy Control of Industrial Systems. The Springer International Series in Engineering and Computer Science, vol 457. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-2813-2_9

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  • DOI: https://doi.org/10.1007/978-1-4757-2813-2_9

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-5055-0

  • Online ISBN: 978-1-4757-2813-2

  • eBook Packages: Springer Book Archive

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