A New Fault-Tolerant Control of Wind Turbine Pitch System Based on ANN Model and Robust and Optimal Development of MRAC Method

Document Type : Original Article

Authors

Faculty of Electrical Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran

Abstract

In this paper, a new method is provided for Fault-Tolerant Control (FTC) of wind turbine pitch systems. One of the common faults in wind turbines is the defects of the pitch sub-system. Each blade of wind turbines tracks a reference signal; it is generated by the main controller unit, defects of actuators, or disturbance decrease of the reference signal quality. Classic controllers cannot deal with the disturbance and compensate for the faults to maintain system performance in normal operating conditions. For this purpose, a novel method based on Optimal Robust Model Reference Adaptive Control (ORMRAC) is presented, the output of the proposed method is a new adaptive rule. The ORMRAC method is robust, optimal, and fast at the same time. The proposed structure includes Fault Detection (FD) and FTC units. FD acts based on the generation and evaluation of residuals. The residual generation is based on Artificial Neural Network (ANN) model. When there is disturbance or fault in the pitch system and residual exceeds the certain threshold, the FT unit is activated. The proposed FT method is tested and evaluated using a wind turbine simulator based on practical data. The results indicated the proper performance of the proposed method in comparison with conventional MRAC and some other methods.

Keywords

References

[1] A. Dameshghi, MH. Refan, “A new strategy for short-term power-curve prediction of wind turbine based on PSO-LS-WSVM”, IJEEE, vol. 14, no. 4, pp. 392-403, 2018.
[2] M. Rahimi, M.R. Esmaeili, “Power controller design and damping improvement of torsional oscillations in the 710 kW DFIG based wind turbine installed at the Binalood site,” Tabriz Journal of Electrical Engineering, vol. 46, no. 4, pp. 123-134, 2 (In persian).
[3] A. Dameshghi, M.H. Refan, P. Amiri, “Wind turbine doubly fed induction generator rotor electrical asymmetry detection based on an adaptive least mean squares filtering of wavelet transform”, Wind Engineering, vol. 10, no. 3, pp. 11-22, 2019.
[4] A. Dameshghi, M.H. Refan, “Combination of condition monitoring and prognosis systems based on current measurement and PSO-LS-SVM method for wind turbine DFIGs with rotor electrical asymmetry”, Energy Systems, pp. 1-30, 2019.
[5] Z. Jiang, M. Karimirad, T. Moan, “Dynamic response analysis of wind turbines under blade pitch system fault, grid loss, and shutdown events”, Wind Energy, vol. 17, no. 9, pp. 1385-1409, 2014.
[6] Y. Shabboei, A. Rikhtegari, S. Khanmohammadi, “Design of Fault Tolerant Nonsingular Terminal Sliding Mode Control for Nonlinear Systems based on an Adaptive Extended Kalman Filter,” vol. 46, no. 4, pp. 173-183, 2016 (In persian).
[7] H. Schulte, E. Gauterin, “Fault-tolerant control of wind turbines with hydrostatic transmission using Takagi–Sugeno and sliding mode techniques”, Annual Reviews in Control, vol. 40, pp. 82-92, 2015.
[8] J. Lan, R. J. Patton, X. Zhu, “Fault-tolerant wind turbine pitch control using adaptive sliding mode estimation”, Renewable Energy, vol. 116, pp. 219-231, 2018.
[9] H. Badihi, Y. Zhang, H, Hong, “Fault-tolerant cooperative control in an offshore wind farm using model-free and model-based fault detection and diagnosis approaches”, Appl Energ, vol. 201, pp. 284-307, 2016.
[10] L. Jalali, M. R. Nezhad-Ahmadi, M. Gohari, P. Bigelow, S. McColl, “The impact of psychological factors on self-reported sleep disturbance among people living in the vicinity of wind turbines”, Environmental Research, vol. 148, pp. 401-410, 2016.
[11] H. Badihi, Y. Zhang, H. Hong, “Model-based Active Fault-tolerant Cooperative Control in an Offshore Wind Farm”, Energy Procedia, vol. 103, pp. 46-51, 2016.
[12] E. B. Muhando, T. Senjyu, A. Uehara, “Gain-Scheduled H∞ Control for WECS via LMI Techniques and Parametrically Dependent Feedback Part II: Controller Design and Implementation”, IEEE T IND ELECTRON, vol. 58, no. 1, pp. 57-68, 2010.
[13] M. Mirzaei, H. H, Niemann, N. K. Poulsen, “A μ-synthesis approach to robust control of a wind turbine”, 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), 2011, Orlando, FL.
[14] M. Mirzaei, M. Soltani, K. Poulsen, H. H. Niemann, “An MPC approach to individual pitch control of wind turbines using uncertain LIDAR measurements”, European Control Conference (ECC), Zurich INSPEC. 2013. Accession Number: 13950748.
[15] M. L. Corradini, G. Ippoliti, G. Orlando, “Robust Control of Variable-Speed Wind Turbines Based on an Aerodynamic Torque Observer”, IEEE T CONTR SYST T, vol. 21, no. 4, pp. 1199-1206, 2013.
[16] L. Danyong, S. Yongduan, C. Wenchuan, H. Karimi, “Wind Turbine Pitch Control and Load Mitigation Using an L1 Adaptive Approach”, Mathematical Problems in Engineering, 2014. 
[17] D. Corcuera, A. Pujana, A. Ezquerra, M. Segurola, E. Landaluze, “H∞ Based Control for Load Mitigation in Wind Turbines”, Energies, vol. 5, no. 4, pp. 938-967, 2012.
[18] L. L. Fan, Y. D, Song, “Neuro-Adaptive Model-Reference Fault- Tolerant Control with Application to Wind Turbines”, IET Control Theory & Applications, vol. 6, no. 4, pp. 475-486, 2012.
[19] E. Kamal, A. Aitouche, R. Ghorbani, M. Bayart, “Robust Fuzzy Fault-Tolerant Control of Wind Energy Conversion Systems subject to Sensor Faults”, IEEE Transactions on Sustainable Energy, vol. 3, no. 2, pp. 231-241, 2012.
[20] C. Sloth, T. Esbensen, J. Stoustrup, “Robust and Fault-Tolerant Linear Parameter-Varying Control of Wind Turbines”, Mechatronics, vol. 21, no. 4, pp. 645-659, 2011.
[21] H. Badihi, Y. M. Zhang, H. Hong, “Fuzzy Gain-Scheduled Active Fault-Tolerant Control of a Wind Turbine”, J FRANKLIN I, vol. 351, no. 7, pp. 3677-3706, 2014.
[22] S. Simani, P. Castaldi, “Data–Drive Design of Fuzzy Logic Fault Tolerant Control for a Wind Turbine Benchmark”, IFAC Proceedings, vol. 45, no. 20, pp. 108-113, 2012.
[23] S. Simani, S. Farsoni, P. Castaldi, “Fault-Tolerant Control of an Offshore Wind Farm via Fuzzy Modelling and Identification”, IFAC-Papers OnLine, vol. 48, no. 21, pp. 1345-1350, 2015.
[24] H. Badihi, Y. Zhang, H. Hong, “Model Reference Adaptive Fault-Tolerant Control for a Wind Turbine against Actuator Faults”, Conference on Control and Fault-Tolerant Systems (SysTol), October 2013 Nice, France.
[25] Y. Vidal, Ch. Tutivén, J. Rodellar, L. Acho, “Fault Diagnosis and Fault-Tolerant Control of Wind Turbines via a Discrete Time Controller with a Disturbance Compensator”, Energies, vol. 8, no. 5, pp. 4300-4316, 2015.
[26] F. Shi, R. Patton, “An active fault tolerant control approach to an offshore wind turbine model”, Renewable Energy, vol. 75, pp. 788-798, 2014.
[27] S. Cho, Z. Gao, T. Moan, “Model-based fault detection, fault isolation and fault-tolerant control of a blade pitch system in floating wind turbines”, Renewable Energy, vol. 120, pp. 306-321, 2018.
[28] H. Badihi, Y. Zhang, S. Rakheja, P. Pillay, “Model-Based Fault-Tolerant Pitch Control of an Offshore Wind Turbine”, IFAC-PapersOnLine, vol. 51, no. 18, pp. 221-226, 2018.
[29] H. Badihi, Y. Zhang, “Fault-tolerant individual pitch control of a wind turbine with actuator faults”, IFAC-PapersOnLine, vol. 51, no. 24, pp. 1133-1140, 2018.
[30] J. Lan, R. J. Patton, X. Zhu, “Fault-tolerant wind turbine pitch control using adaptive sliding mode estimation”, Renewable Energy, vol. 116, pp. 219-231, 2018.
[31] Y. Liu, R. J. Patton, J. Lan, J. “Fault-tolerant Individual Pitch Control using Adaptive Sliding Mode Observer”, IFAC-PapersOnLine, vol. 51, no. 24, pp. 1127-1132, 2018.
[32] S. Mullick, “Design of Model Reference Adaptive Controller with Multiplicative Structured Uncertainty”, Msc Thesis, Jadavpur University, 2012.
[33] J. Nelson, M. J Balas, R. S Erwin, “Model Reference Adaptive Control of Mildly Non-Linear Systems with Time Varying Input Delays – Part I”, Advances in Aerospace Guidance, Navigation and Control, 2013.
[34] K.S Narendra, M. Annaswamy, “A new adaptive law for robust adaptation without persistent excitation”, IEEE T AUTOMAT CONTR, vol. 32, no. 2, pp. 134-145, 1987.
[35] T. Nguyen, “Optimal control modification for robust adaptive control with large adaptive gain”, Syst Control Lett, vol. 61, no. 4, pp. 485-494, 2012.
[36] T. Zhang, S. S Ge, C. C. Hang, “Adaptive control of first-order systems with nonlinear parameterization”, IEEE T AUTOMAT CONTR, vol. 45, no. 8, pp. 1512-1516, 2000.
[37] P.A. Ioannou, V. Kokotovic, “Instability analysis and improvement of robustness of adaptive control”, Automatica, vol. 20, no. 5, pp. 583-594, 1984.
[38] K. Khalil, J. W. Grizzle, “Nonlinear systems,” vol. 3. New Jersey: Prentice hall, 1996.
[39] G. Cybenko, “Approximation by superpositions of a sigmoidal function”, MCSS, vol. 2, no. 4, pp. 303-314, 1989.
[40] C.A. Micchelli, “Interpolation of scattered data: distance matrices and conditionally positive definite functions”, Constructive Approximation, vol. 2, no. 1, pp. 11-22, 1986.
[41]  A.J. Calise, T. Yucelen, “Adaptive Loop Transfer Recovery”, JGCD, vol. 35, no. 3, pp. 807-815, 2012.
[42] Mapna 2.5 MW (Mapna Group) Wind Turbine available at [http://www.thewindpower.net/turbine_en_986_mapna-group_2500.php]
[43]  F. A. Inthamoussou, F. B Bianchi, R. J. Mantz, “LPV Wind Turbine Control with Anti-Windup Features Covering the Complete Wind Speed Range”, IEEE T Energy Conver, vol. 29, no.1, pp. 259-266, 2014.

Files

Share

How to cite

Statistics