Takagi-Sugeno fuzzy modelling and robust fault reconstruction for wind turbine systems

Xiaoxu Liu, Zhiwei Gao

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

4 Citations (Scopus)

Abstract

In this study, a robust fault reconstruction approach is proposed for the 4.8 MW wind turbine benchmark system. Firstly, through weighted combination of a number of locally valid linear systems, the nonlinear wind turbine model is well represented by a Takagi-Sugeno fuzzy model. Then, augmented system approach jointly with unknown input fuzzy observer technique are utilized to estimate faults and system states simultaneously, while decouple a part of unknown inputs which consist both system perturbations and Takagi-Sugeno modelling errors. After that, linear matrix inequality approach is used to ensure convergence of estimation error and attenuate the influences from un-decoupled unknown inputs. Finally, the proposed algorithms are demonstrated to be effective by using the 4.8 MW wind turbine benchmark system.
Original languageEnglish
Title of host publicationProceedings of the 2016 IEEE 14th International Conference on Industrial Informatics (INDIN)
PublisherIEEE
Pages492-495
ISBN (Print)978-1-5090-2870-2
DOIs
Publication statusPublished - 19 Jan 2017
Event14th International Conference on Industrial Infomatics (INDIN 2016) - Poitiers, France
Duration: 19 Jan 2017 → …

Conference

Conference14th International Conference on Industrial Infomatics (INDIN 2016)
Period19/01/17 → …

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