Nonlinear Fuzzy Model Predictive Control of a Class of Chaotic Systems

  • Weijie Wang
  • , Yongmei Gan
  • , Bin Wang
  • , Xia Zhao
  • , Qian Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

A novel fuzzy based model predictive control strategy using fuzzy model is investigated in order to provide a new view about how to design a controller for a class of chaotic systems. At the beginning of this study, a class of chaotic system's Takagi-Sugeno model is presented, then linearized system model can be changed in form of augmented state space model. By the combination of fuzzy linearization technique and linear model predictive control method, a new controller concerning fuzzy and predictive control strategy is designed for a class of chaotic systems, and the detailed theoretical proof is presented. Numerical simulations including two-dimensional non-autonomous chaotic power system and three-dimensional double-wing autonomous chaotic system are shown in this paper. The presented simulation result shows the chaotic system reaches the steady state quickly which proves the suggested scheme's effectiveness and universality.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE International Power Electronics and Application Conference and Exposition, PEAC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538660539
DOIs
StatePublished - 26 Dec 2018
Event2018 IEEE International Power Electronics and Application Conference and Exposition, PEAC 2018 - Shenzhen, China
Duration: 4 Nov 20187 Nov 2018

Publication series

NameProceedings - 2018 IEEE International Power Electronics and Application Conference and Exposition, PEAC 2018

Conference

Conference2018 IEEE International Power Electronics and Application Conference and Exposition, PEAC 2018
Country/TerritoryChina
CityShenzhen
Period4/11/187/11/18

Keywords

  • Takagi-Sugeno fuzzy model
  • model predictive control
  • nonlinear chaotic systems

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