Neuro-Fuzzy Modeling and Control

Jyh Shing Roger Jang, Chuen-Tsai Sun

Research output: Contribution to journalArticlepeer-review

1751 Scopus citations

Abstract

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 certain advantages over neural networks. We introduce the design methods for ANFIS in both modeling and control applications. Current problems and future directions for neuro-fuzzy approaches are also addressed.

Original languageEnglish
Article number364486
Pages (from-to)378-406
Number of pages29
JournalProceedings of the IEEE
Volume83
Issue number3
DOIs
StatePublished - Mar 1995

Keywords

  • ANFIS
  • Fuzzy logic
  • fuzzy modeling
  • neural networks
  • neuro-fuzzy control
  • neuro-fuzzy modeling

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