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

Liu, Xiaoxu and Gao, Zhiwei (2017) Takagi-Sugeno fuzzy modelling and robust fault reconstruction for wind turbine systems. In: Proceedings of the 2016 IEEE 14th International Conference on Industrial Informatics (INDIN). IEEE, pp. 492-495. ISBN 978-1-5090-2870-2

Full text not available from this repository. (Request a copy)
Official URL: http://dx.doi.org/10.1109/INDIN.2016.7819211

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.

Item Type: Book Section
Uncontrolled Keywords: robust fault reconstruction, Wind turbines, Takagi-Sugeno fuzzy model
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Physics and Electrical Engineering
Depositing User: Ay Okpokam
Date Deposited: 25 Jan 2017 14:38
Last Modified: 06 Feb 2017 09:18
URI: http://nrl.northumbria.ac.uk/id/eprint/29354

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics


Policies: NRL Policies | NRL University Deposit Policy | NRL Deposit Licence