Fault Reconstruction and State Estimation for Large-Scale T-S Fuzzy System

Van Phong Vu, Wen June Wang, Van Thuyen Ngo, Dinh Thanh Ngo, Huu Thai Pham

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

Abstract

This paper proposes a new approach to designing the observer for the nonlinear Large-scale system. The nonlinear large-scale system is modeled under the T-S fuzzy system framework that allows us to apply powerful linear methodologies to synthesize the observer. The interconnection terms of considered large-scale T-S fuzzy systems are unknown and do not need to satisfy any constraint. In addition, both the system and sensor of the large-scale T-S fuzzy system are impacted by the fault. A decentralized fuzzy observer is designed to estimate the unknown states as well as reconstruct the fault, simultaneously. With the support of the augment technique, Lyapunov methodology, and Linear Matrix Inequality (LMIs) technique, the conditions for observer design are derived in the main theorems. Finally, a numerical example is provided to show the effectiveness and merit of the proposed method.

Original languageEnglish
Title of host publicationComputational Intelligence Methods for Green Technology and Sustainable Development - Proceedings of the International Conference GTSD2022
EditorsYo-Ping Huang, Wen-June Wang, Hoang An Quoc, Hieu-Giang Le, Hoai-Nam Quach
PublisherSpringer Science and Business Media Deutschland GmbH
Pages556-568
Number of pages13
ISBN (Print)9783031196935
DOIs
StatePublished - 2023
Event6th International Conference on Green Technology and Sustainable Development, GTSD 2022 - Nha Trang city, Viet Nam
Duration: 29 Jul 202230 Jul 2022

Publication series

NameLecture Notes in Networks and Systems
Volume567 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference6th International Conference on Green Technology and Sustainable Development, GTSD 2022
Country/TerritoryViet Nam
CityNha Trang city
Period29/07/2230/07/22

Keywords

  • Fault estimation
  • LMIs
  • Large-scale T-S fuzzy system
  • Observer design

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