Optimization of Fuzzy Membership Function based on the NCOS function method

Jingying Li, Xingjian Jing, Zhengchao Li, Xianlin Huang

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


This paper investigates the parameter optimization problem of membership functions for fuzzy-model-based control under imperfect premise matching. A novel frequency domain algorithm which can clearly relate the membership function parameters to the targeted control performance is developed, and consequently an optimization approach to the membership function parameters is then established based on the resulting nonlinear characteristic output spectrum function (nCOS). Compared to traditional search-based optimization approach, this method can give a more detailed result with less time consuming and an in-depth understanding of nonlinear influence rather than just optimal results. With this novel method, performance of the fuzzy-model-based controller is further enhanced. Finally, the fuzzy membership functions optimization method is applied to nonlinear systems to obtain improved system performance.

Original languageEnglish
Title of host publicationProceedings - IECON 2020
Subtitle of host publication46th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE Computer Society
Number of pages6
ISBN (Electronic)9781728154145
Publication statusPublished - 18 Oct 2020
Event46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020 - Virtual, Singapore, Singapore
Duration: 19 Oct 202021 Oct 2020

Publication series

NameIECON Proceedings (Industrial Electronics Conference)


Conference46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020
CityVirtual, Singapore


  • frequency domain method
  • Membership function optimization

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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