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ABSTRACT
This research investigates the synthesis of a new Finite Frequency Observer (FFO) to detect faults affecting wind turbines. First, the wind turbine nonlinear behaviour is approximated using Takagi-Sugeno (T-S) fuzzy modelling technique for observer design purposes. Then, through the H-/H∞ optimisation technique with Finite Frequency (FF) specification, the FFO design conditions are formulated using the Lyapunov method as a set of LMIs. Finally, to assess the efficiency of the FFO-based detection approach, simulations results are applied to a dynamic 4.8 MW WT model, where an Unknown Input Observer method is used for comparison.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Bouchra Sefriti
Bouchra SEFRITI received her Ph.D. degree in 2016 from Sidi Mohammed ben Abdellah. His research focuses on fault detection and isolation in renewable energy systems, fuzzy logic and robust control of nonlinear systems.
Ayoub El Bakri
Ayoub El Bakri is currently assistant professor in the department of physics at the faculty of sciences Dhar El Mehraz. He received his Ph.D. degree in 2019 from Sidi Mohammed ben Abdellah. His research focuses on fault detection and isolation in nonlinear systems with application to the wind turbine, machine learning and robust control of nonlinear systems.
Selma Sefriti
Selma Sefriti is currently assistant professor in the Department of physics at the faculty of sciences Dhar El Mehraz. She received her Ph.D. degree in 2013 from Sidi Mohammed ben Abdellah.her research interests include robust control of nonlinear systems and fuzzy logic control.
Ismail Boumhidi
Ismail Boumhidi is a professor of electronics at the Faculty of Sciences, Fez, Morocco. He received his Ph.D. degree in 1999 from Sidi Mohammed ben Abdellah University. His research areas include adaptive robust control, multivariable non-linear systems and fuzzy logic control with applications.