DocumentCode
128681
Title
Robust observer-based fault detection via evolutionary optimization with applications to wind turbine systems
Author
Yongjia Zhu ; Zhiwei Gao
Author_Institution
Fac. of Math. & Phys. Sci., Univ. of Coll. London, London, UK
fYear
2014
fDate
9-11 June 2014
Firstpage
1627
Lastpage
1632
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.
Keywords
eigenvalues and eigenfunctions; evolutionary computation; genetic algorithms; observers; power generation control; robust control; wind turbines; evolutionary optimal algorithms; parameter eigenvalue assignment; power 3 MW; robust fault detection filter; robust observer based fault detection; wind turbine systems; Actuators; Eigenvalues and eigenfunctions; Fault detection; Observers; Optimization; Robustness; Wind turbines; fault diagnosis; genetic algorithm; parameter eigenvalue assignment; robust observer design; wind turbine systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics and Applications (ICIEA), 2014 IEEE 9th Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-4799-4316-6
Type
conf
DOI
10.1109/ICIEA.2014.6931428
Filename
6931428
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