Robust Observer-Based Fault Detection via Evolutionary Optimization with Applications to Wind Turbine Systems

Zhu, Yongjia and Gao, Zhiwei (2014) Robust Observer-Based Fault Detection via Evolutionary Optimization with Applications to Wind Turbine Systems. In: IEEE 9th Conference on Industrial Electronics and Applications (ICIEA), 9-11 June, 2014, Hangzhou.

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Abstract

In this paper, a robust fault detection filter is designed for a 3MW wind turbine system. The parameter eigenvalue assignment approaches and evolutionary optimal algorithms are integrated to seek optimal observer gain such that the residual signal is sensitive to the fault, but robustness against the disturbances. From all the simulations, the performance of fault detections is satisfactory.

Item Type: Conference or Workshop Item (Speech)
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Related URLs:
Depositing User: Zhiwei Gao
Date Deposited: 15 Jul 2014 09:32
Last Modified: 24 Oct 2017 08:52
URI: http://nrl.northumbria.ac.uk/id/eprint/17195

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