Robust fault tolerant control for drive train in wind turbine systems with stochastic perturbations

Xiaoxu Liu, Zhiwei Gao, Aihua Zhang, Yanling Li

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

1 Citation (Scopus)

Abstract

To achieve reliable operation of wind energy conversion technology, this ρ aper develops a robust observer-based fault tolerant control technique for wind turbine drive train systems in presence of simultaneous unknown inputs, faults and Brownian perturbations. Integration of several advanced techniques, namely, augmented approach, unknown input observer method, and linear matrix inequaity, is employed to estimate the means of the system states and the considered faults robustly. Based on the estimates, robust fault tolerant control strategy is implemented to drive the system trajectory convergent and eliminate the effects of faults from both actuators and sensors successfully. The control gains are selected to guarantee the convergence of the means of system states and com pens ate for the de grad ation caused by concerned faults. The ob server gain is determined via a linear matrix inequality optimization such that the closed-loop system is stochastically input-to-state stable satisfying required robust performance. The desi gned observer-based fault tolerant control c an make the over all system work in a steady condition and the system outputs c an be compensated to successfully track the healthy outputs in fault-free c ases. Finally, the proposed fault estimation-based fault tolerant control method is applied to a drive train system of the 4.8 MW benchmark wind wind turbine to validate the effectiveness.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE 15th International Conference on Industrial Informatics, INDIN 2017
PublisherIEEE
Pages677-680
Number of pages4
ISBN (Electronic)9781538608371
DOIs
Publication statusPublished - 10 Nov 2017
Event15th IEEE International Conference on Industrial Informatics, INDIN 2017 - Emden, Germany
Duration: 24 Jul 201726 Jul 2017

Publication series

NameProceedings - 2017 IEEE 15th International Conference on Industrial Informatics, INDIN 2017

Conference

Conference15th IEEE International Conference on Industrial Informatics, INDIN 2017
Country/TerritoryGermany
CityEmden
Period24/07/1726/07/17

Keywords

  • Brownian perturbations
  • fault estimation
  • fault tolerant control
  • stockastic input-to-state stability
  • stockastic system

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