Progress in on-line adaptive, learning and evolutionary strategies for fuzzy logic control

Minrui Fei, Siu Lau Ho

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

Abstract

In this paper, the eight kinds of on-line adaptive, learning and evolutionary strategies for fuzzy logic control are systematically introduced. All these afore-mentioned strategies have some drawbacks in terms of generalization and formulation. Hence a systematic way of combination and hybridization of these strategies will be very useful for improving the learning capacity and performance of algorithms based on these strategies. It is concluded that the orientation of deep-going pathfinding in the generation and modification of fuzzy control rules or models which is principally based on neural networks combined with genetic algorithms or other algorithms should be able to compensate for the disadvantages of neural networks learning.
Original languageEnglish
Title of host publicationProceedings of the International Conference on Power Electronics and Drive Systems
PublisherIEEE
Pages1108-1113
Number of pages6
Publication statusPublished - 1 Dec 1999
Externally publishedYes
EventProceedings of the 1999 3rd IEEE International Conference on Power Electronics and Drive Systems (PEDS'99) - Kowloon, Hong Kong
Duration: 27 Jul 199929 Jul 1999

Conference

ConferenceProceedings of the 1999 3rd IEEE International Conference on Power Electronics and Drive Systems (PEDS'99)
CountryHong Kong
CityKowloon
Period27/07/9929/07/99

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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