TY - GEN
T1 - Robust fault tolerant control for drive train in wind turbine systems with stochastic perturbations
AU - Liu, Xiaoxu
AU - Gao, Zhiwei
AU - Zhang, Aihua
AU - Li, Yanling
N1 - Publisher Copyright:
© 2017 IEEE.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2017/11/10
Y1 - 2017/11/10
N2 - To achieve reliable operation of wind energy conversion technology, this ρ aper develops a robust observer-based fault tolerant control technique for wind turbine drive train systems in presence of simultaneous unknown inputs, faults and Brownian perturbations. Integration of several advanced techniques, namely, augmented approach, unknown input observer method, and linear matrix inequaity, is employed to estimate the means of the system states and the considered faults robustly. Based on the estimates, robust fault tolerant control strategy is implemented to drive the system trajectory convergent and eliminate the effects of faults from both actuators and sensors successfully. The control gains are selected to guarantee the convergence of the means of system states and com pens ate for the de grad ation caused by concerned faults. The ob server gain is determined via a linear matrix inequality optimization such that the closed-loop system is stochastically input-to-state stable satisfying required robust performance. The desi gned observer-based fault tolerant control c an make the over all system work in a steady condition and the system outputs c an be compensated to successfully track the healthy outputs in fault-free c ases. Finally, the proposed fault estimation-based fault tolerant control method is applied to a drive train system of the 4.8 MW benchmark wind wind turbine to validate the effectiveness.
AB - To achieve reliable operation of wind energy conversion technology, this ρ aper develops a robust observer-based fault tolerant control technique for wind turbine drive train systems in presence of simultaneous unknown inputs, faults and Brownian perturbations. Integration of several advanced techniques, namely, augmented approach, unknown input observer method, and linear matrix inequaity, is employed to estimate the means of the system states and the considered faults robustly. Based on the estimates, robust fault tolerant control strategy is implemented to drive the system trajectory convergent and eliminate the effects of faults from both actuators and sensors successfully. The control gains are selected to guarantee the convergence of the means of system states and com pens ate for the de grad ation caused by concerned faults. The ob server gain is determined via a linear matrix inequality optimization such that the closed-loop system is stochastically input-to-state stable satisfying required robust performance. The desi gned observer-based fault tolerant control c an make the over all system work in a steady condition and the system outputs c an be compensated to successfully track the healthy outputs in fault-free c ases. Finally, the proposed fault estimation-based fault tolerant control method is applied to a drive train system of the 4.8 MW benchmark wind wind turbine to validate the effectiveness.
KW - Brownian perturbations
KW - fault estimation
KW - fault tolerant control
KW - stockastic input-to-state stability
KW - stockastic system
UR - http://www.scopus.com/inward/record.url?scp=85041174624&partnerID=8YFLogxK
U2 - 10.1109/INDIN.2017.8104853
DO - 10.1109/INDIN.2017.8104853
M3 - Conference contribution
AN - SCOPUS:85041174624
T3 - Proceedings - 2017 IEEE 15th International Conference on Industrial Informatics, INDIN 2017
SP - 677
EP - 680
BT - Proceedings - 2017 IEEE 15th International Conference on Industrial Informatics, INDIN 2017
PB - IEEE
T2 - 15th IEEE International Conference on Industrial Informatics, INDIN 2017
Y2 - 24 July 2017 through 26 July 2017
ER -