Uncertainty reasoning based on cloud models in controllers

D. Li, D. Cheung, Xuemei Shi, Vincent To Yee Ng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

244 Citations (Scopus)

Abstract

The methodology of fuzzy reasoning has been shown to be very useful technology for modeling complex nonlinear systems. However, the most commonly used method for reasoning with fuzzy systems models, the Mamdani-Zadeh paradigm, faces many criticisms, particularly from the probability community. A new mathematical representation of linguistic concepts is presented in this paper. With the new model of normal compatibility clouds and a virtual rule engine, a novel uncertainty reasoning technology is proposed. It not only serves as a foundation of linguistic control, but also integrating fuzziness and randomness in an inseparable way. A case study is given to clean up many doubts raised in the debate between fuzzy theory and probability theory researchers, and to give a good interpretation of the Mamdani-Zadeh operations for the defuzzification strategy as well. The architecture of such a controller shows the advantages in hardware implementations.
Original languageEnglish
Pages (from-to)99-123
Number of pages25
JournalComputers and Mathematics with Applications
Volume35
Issue number3
DOIs
Publication statusPublished - 1 Jan 1998

Keywords

  • Cloud generator
  • Compatibility cloud
  • Linguistic atom
  • Uncertainty modeling
  • Virtual cloud

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computational Theory and Mathematics
  • Computational Mathematics

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