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Finite-time fault detection and reconstruction of permanent magnet synchronous generation wind turbine via sliding mode observer. (English) Zbl 1537.93125

Summary: In this study, a method for fault detection of a permanent magnet synchronous generator (PMSG) wind turbine is proposed. The dynamic model of the wind energy conversion system is simulated and the system’s fault is diagnosed using a proposed terminal sliding mode observer (TSMO). The nonlinear state-space equations of the closed-loop wind turbine are derived, which include a robust adaptive controller that is implemented for maximum power capture and a PI controller that is designed for pitch angle control. Then, utilising a new approach, a TSMO is designed for estimating the states and faults in a finite time. The stability and convergence of the states and fault estimation error are investigated via the Lyapunov stability theory. A \(3kw\) PMSG wind turbine is simulated and using TSMO the states are estimated and a blade imbalance fault (BIF) fault is detected. The state and fault estimation errors converge to zero in a finite time.

MSC:

93B12 Variable structure systems
93B53 Observers
93C40 Adaptive control/observation systems
93C95 Application models in control theory
Full Text: DOI

References:

[1] Ahmad, M., & Mohd-Mokhtar, R. (2021). Model matching fault detection filter design for a linear discrete-time system with mixed uncertainties. International Journal of Control, 96(2), 449-460. . · Zbl 1518.93139
[2] Baburajan, S. (2018, February 06-April 05). Improving the efficiency of a wind turbine system using a fuzzy-pid controller. Advances in Science and Engineering Technology International Conferences (ASET), . IEEE.
[3] Boulouma, S., Belmili, H., & Labiod, S. (2015, December 13-15). Robust adaptive maximum power capture control scheme for a PMSG based WECS. 4th international Conference on Electrical Engineering, ICEE 2015, . IEEE. .
[4] Corradini, M. L., Cristofaro, A., & Pettinari, S. (2014, June 24-27). Diagnosis and accommodation of faults affecting the PMSG in variable-speed sensorless wind turbines - A deterministic approach. European Control Conference, ECC 2014, (pp. 1957-1962). IEEE.
[5] Freire, N. M. A., Estima, J. O., & Cardoso, A. J. M. (2012). A new approach for current sensor fault diagnosis in PMSG drives for wind energy conversion systems. IEEE Energy Conversion Congress and Exposition (pp. 2083-2090). IEEE. .
[6] Gao, Z., & Liu, X. (2021). An overview on fault daignosis, prognosis and resilient control for wind turbine systems. processes, 9(2), 300. .
[7] Gong, X., & Qiao, W. (2012). Imbalance fault detection of direct-drive wind turbines using generator current signals. IEEE Transactions on Energy Conversion, 27(2), 468-476. .
[8] Hang, J., Zhang, J., & Cheng, M. (2014, September 14-18). Fault diagnosis of wind turbine using control loop current signals. IEEE Energy Conversion Congress and Exposition (ECCE), (pp. 3119-3124). IEEE.
[9] He, W., Xiang, W., He, X., & Li, G. (2020). Boundary vibration control of a floating wind trubine system with mooring lines. Control Engineering Practice, 101, 104423. .
[10] Khodakaramzadeh, S., Ayati, M., & Ha’iri-Yazdi, M. R. (2021). Fault diagnosis of a permanent magnet synchronous generator wind turbine. Journal of Electrical and Computer Engineering Innovations, 9(2), 143-152.
[11] Lu, B., Li, Y., Wu, X., & Yang, Z. (2009). A review of recent advances in wind turbine condition monitoring and fault diagnosis. IEEE Power Electronics and Machines in Wind Applications.
[12] Lu, D., & Qiao, W. (2013, June 16-19). Frequency demodulation-aided condition monitoring for drivetrain gearboxes. IEEE Transportation Electrification Conference and Expo (ITEC), . IEEE.
[13] Malik, H., & Mishra, S. (2015). Application of LVQ network in fault diagnosis of wind turbine using TurbSim, FAST and simulink. 2015. Michael Faraday IET International Summit (pp. 474-480). IET. .
[14] Malik, H., & Mishra, S. (2016a, November 25-27). Application of fuzzy Q learning (FQL) technique to wind turbine imbalance fault identification using generator current signals. IEEE 7th Power India International Conference (PIICON), . IEEE.
[15] Malik, H., & Mishra, S. (2016b, November 17-19). Application of gene expression programming (GEP) to investigate the health condition of direct-drive wind turbine. 7th India International Conference on Power Electronics (IICPE), . IEEE.
[16] Miryousefi Aval, S. M., & Ahadi, A. (2016). Wind turbine fault diagnosis techniques and related algorithms. International Journal of Renewable Energy Research, 6(1), 80-89. .
[17] Mosa, M. A., Elsyed, A. A., Amin, A. M. A., & Ghany, A. M. A. (2016). Variable speed wind turbine pitch angle controller with rate limiter anti-windup. Eighteenth International Middle East Power Systems Conference (MEPCON), . Variable speed wind turbine pitch angle controller with rate limiter anti-windup. IEEE.
[18] Mousavi, M., Rahnavard, M., Ayati, M., & Hairi Yazdi, M. R. (2019). Terminal sliding mode observers for uncertain linear systems with matched disturbance. Asian Journal of Control, 21(1), 377-386. · Zbl 1422.93040
[19] Munteanu, I., Bratcu, A., Cutululis, N., & Ceanga, E. (2008). Optimal control of wind energy systems: Toward a global approach. Springer.
[20] Muyeen, S. M., Tamura, J., & Murata, T. (2009). Stability augmentation of a grid-connected wind farm. Springer.
[21] Nguyen, H. M., & Naidu, D. S. (2012, October 24-26). Direct fuzzy adaptive control for standalone wind energy conversion systems. Proceedings of the World Congress on Engineering and Computer Science, . Newswood Limited.
[22] Odgaard, P. F., & Johnson, K. E. (2013, June 17-19). Wind turbine fault detection and fault tolerant control – an enhanced benchmark challenge. American Control Conference (ACC), (pp. 4447-4452). IEEE. .
[23] Orlando, N. A., Liserre, M., Mastromauro, R. A., & Aquila, A. D. (2013). A survey of control issues in PMSG-based small wind-turbine systems. IEEE Transactions on Industrial Informatics, 9(3), 1211-1221. .
[24] Rahnavard, M., Ayati, M., & Hairi Yazdi, M. R. (2018). Robust actuator and sensor fault reconstruction of wind turbine using modified sliding mode observer. Transactions of the Institute of Measurement and Control, 41(6), 1504-1518. .
[25] Rahnavard, M., Ayati, M., Hairi Yazdi, M. R., & Mousavi, M. (2019). Finite time estimation of actuator faults, states, and aerodynamic load of a realistic wind turbine. Renewable Energy, 28, 256-267. .
[26] Rahnavard, M., Hairi Yazdi, M. R., & Ayati, M. (2017). On the development of a sliding mode observer-based fault diagnosis scheme for a wind turbine benchmark model. Journal of Energy Equipments and Systems, 5(1), 13-26. .
[27] Sales-Setien, E., Penarrocha, I., Dolz, D., & Sanchis, R. (2015). Fault detection in the blade and pitch system of a wind turbine with H2 PI observers. Journal of Physics: Conference Series, 659, 012033. IOP Publishing. .
[28] Simani, S., & Castaldi, P. (2019). Intellifent fault diagnosis techniques applied to an offshore wind turbine system. Applied Sciences, 9(4), 783, .
[29] Tan, C. P., Yu, X., & Man, Z. (2010). Terminal sliding mode observers for a class of nonlinear systems. Automatica, 46(8), 1401-1404. . · Zbl 1204.93025
[30] Tong, X., & Zhao, X. (2017). Power generation control of a monopile hydrostatic wind turbine using an H∞ loop-shaping torque controller and an LPV pitch controller. IEEE Transactions on Control Systems Technology, 26(6), 2165-2172. .
[31] Wang, X., Guo, J., & Lu, S. (2020, August 22-24). A Two-step method for PMSG bearing fault recognition under varying speed condition. Chinese Control and Decision Conference (CCDC), (pp. 5102-5106). IEEE.
[32] Yan, X., & Edwards, C. (2007). Nonlinear robust fault reconstruction and estimation using a sliding mode observer. Automatica, 43(9), 1605-1614. . · Zbl 1128.93389
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