LPV modelling and LPV observer-based fault detection for wind turbine systems

Hui Shao; Zhiwei Gao; Krishna Busawon

doi:10.1109/INDIN.2016.7819206

LPV modelling and LPV observer-based fault detection for wind turbine systems

Hui Shao, Zhiwei Gao, Krishna Busawon

Research output: Contribution to conference › Paper › peer-review

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Abstract

In this paper, linear parameter varying (LPV) modelling technique is addressed for modelling a wind turbine system, with real-time changing scheduling parameters. Based on the LPV wind turbine model, a LPV observer-based fault detection method is utilized to detect faults under four scenarios. The effectiveness of the proposed modelling and fault detection techniques is demonstrated by using the widely-recognized wind turbine benchmark system.

Original language	English
DOIs	https://doi.org/10.1109/INDIN.2016.7819206
Publication status	Published - 20 Jul 2016
Event	INDIN 2016 - 14th IEEE International Conference on Industrial Informatics - Poitiers, France Duration: 20 Jul 2016 → …

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Conference	INDIN 2016 - 14th IEEE International Conference on Industrial Informatics
Period	20/07/16 → …

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10.1109/INDIN.2016.7819206

Cite this

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title = "LPV modelling and LPV observer-based fault detection for wind turbine systems",

abstract = "In this paper, linear parameter varying (LPV) modelling technique is addressed for modelling a wind turbine system, with real-time changing scheduling parameters. Based on the LPV wind turbine model, a LPV observer-based fault detection method is utilized to detect faults under four scenarios. The effectiveness of the proposed modelling and fault detection techniques is demonstrated by using the widely-recognized wind turbine benchmark system.",

author = "Hui Shao and Zhiwei Gao and Krishna Busawon",

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AU - Shao, Hui

AU - Gao, Zhiwei

AU - Busawon, Krishna

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N2 - In this paper, linear parameter varying (LPV) modelling technique is addressed for modelling a wind turbine system, with real-time changing scheduling parameters. Based on the LPV wind turbine model, a LPV observer-based fault detection method is utilized to detect faults under four scenarios. The effectiveness of the proposed modelling and fault detection techniques is demonstrated by using the widely-recognized wind turbine benchmark system.

AB - In this paper, linear parameter varying (LPV) modelling technique is addressed for modelling a wind turbine system, with real-time changing scheduling parameters. Based on the LPV wind turbine model, a LPV observer-based fault detection method is utilized to detect faults under four scenarios. The effectiveness of the proposed modelling and fault detection techniques is demonstrated by using the widely-recognized wind turbine benchmark system.

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M3 - Paper

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Y2 - 20 July 2016

ER -

LPV modelling and LPV observer-based fault detection for wind turbine systems

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UN SDGs

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