Sensorless vector control of doubly fed induction generator based wind turbine using fuzzy fractional order adaptive disturbance rejection control

References

• Abad, G., J. Lopez, M. A. Rodriguez, L. Marroyo, and G. Iwanski. 2011. Doubly fed induction machine: Modeling and control for wind energy generation. Hoboken, New Jersey: Wiley-IEEE Press. doi:10.1002/9781118104965.
   Google Scholar
• Abad, G. 2016. Power electronics and electric drives for traction applications. SPi Global, Pondicherry, India: John Wiley & Sons. doi:10.1002/9781118954454.
   Google Scholar
• Abdelbaset, A., Y. S. Mohamed, A. H. M. El-Sayed, and A. E. H. Abozeid Ahmed. 2018. Wind driven doubly fed induction generator: Grid synchronization and control. Cham, Switzerland: Springer. doi:10.1007/978-3-319-70108-0.
   Google Scholar
• Abdelrahem, M., C. Hackl, and R. Kennel. 2015. Sensorless control of doubly-fed induction generators in variable-speed wind turbine systems. Proceedings of International Conference on Clean Electrical Power ICCEP IEEE, Taormina, Italy, 406–13. doi:10.1109/ICCEP.2015.7177656.
   Google Scholar
• Abdelrahem, M., C. Hackl, and R. Kennel. 2016. Encoderless model predictive control of doubly-fed induction generators in variable-speed wind turbine systems. Journal of Physics. Conference Series 753 (11):1–10. doi:10.1088/1742-6596/753/11/112005.
   Google Scholar
• Abu-Rub, H., M. Malinowski, and K. Al-Haddad. 2014. Power electronics for renewable energy systems, transportation and industrial applications. Wiley-IEEE Press. doi:10.1002/9781118755525.
   Google Scholar
• Ali, M., and C. K. Alexander. 2017. Trajectory tracking control for a robotic manipulator using nonlinear active disturbance rejection control. Proceedings of ASME 2017 Dynamic Systems and Control Conference, Tysons, Virginia, USA, 1–8. doi:10.1115/DSCC2017-5088.
   Google Scholar
• Bartolini, G., A. Ferrara, E. Usai, and V. I. Utkin. 2000. On multi-input chattering-free second-order sliding mode control. IEEE Transactions on Automatic Control 45 (9):1711–17. doi:10.1109/9.880629.
   Web of Science ®Google Scholar
• Belmokhtar, K., M. Doumbia, and K. Agbossou. 2014. Novel fuzzy logic based sensorless maximum power point tracking strategy for wind turbine systems driven DFIG (doubly-fed induction generator). Energy Elsevier 76:679–93. doi:10.1016/j.energy.2014.08.066.
   Google Scholar
• Blaabjerg, F., M. Liserre, and K. Ma. 2012. Power electronics converters for wind turbine systems. IEEE Transactions on Industry Applications 48 (2):708–19. doi:10.1109/TIA.2011.2181290.
   Web of Science ®Google Scholar
• Bossoufi, B., M. Karim, A. Lagriou, M. Taoussi, and A. Derouich. 2015. Observer backstepping control of DFIG-generators for wind turbines variable-speed: FPGA-based implementation. Renewable Energy Elsevier 81:903–17. doi:10.1016/j.renene.2015.04.013.
   Web of Science ®Google Scholar
• Bouderbala, M., B. Bossoufi, A. Lagrioui, M. Taoussi, H. A. Aroussi, and Y. Ihedrane. 2018. Direct and indirect vector control of a doubly fed induction generator based in a wind energy conversion system. International Journal of Electrical and Computer Engineering IJECE 9 (3):1531–40. doi:10.11591/ijece.v9i3.pp1531-1540.
   Google Scholar
• Boukhriss, A., T. Nasser, and A. Essadki. 2013. A linear active disturbance rejection control applied for DFIG based wind energy conversion system. International Journal of Computer Science Issues IJCSI 10 (2):391–99.
   Google Scholar
• Boukhriss, A., A. Essadki, A. Bouallouch, and T. Nasser. 2014. Maximization of generated power from wind energy conversion systems using a doubly fed induction generator with active disturbance rejection control. Proceedings of 2nd World Conference on Complex Systems WCCS, Agadir, Morocco, 330–35. doi:10.1109/ICoCS.2014.7060907.
   Google Scholar
• Cardenas, R., and R. Pena. 2004. Sensorless vector control of induction machines for variable-speed wind energy applications. IEEE Transactions on Energy Conversion 19 (1):196–205. doi:10.1109/TEC.2003.821863.
   Web of Science ®Google Scholar
• Cardenas, R., R. Pena, J. Clare, G. Asher, and J. Proboste. 2008. MRAS observers for sensorless control of doubly-fed induction generators. IEEE Transactions on Power Electronics 23 (3):1075–84. doi:10.1109/TPEL.2008.921189.
   Web of Science ®Google Scholar
• Chen, S. Z., N. C. Cheung, K. C. Wong, and J. Wu. 2011. Integral variable structure direct torque control of doubly fed induction generator. IET Renewable Power Generation 5 (1):18–25. doi:10.1049/iet-rpg.2009.0021.
   Web of Science ®Google Scholar
• Chen, G., L. Zhang, and X. Cai. 2014. Optimized control of the doubly fed induction generator system based on input–output linearizing scheme. Wind Engineering 38 (1):101–08. doi:10.1260/0309-524X.38.1.101.
   Google Scholar
• Comanescu, M., and L. Xu. 2006. Sliding-mode MRAS speed estimators for sensorless vector control of induction machine. IEEE Transactions on Industrial Electronics 53 (1):146–53. doi:10.1109/TIE.2005.862303.
   Web of Science ®Google Scholar
• Da Costa, J. P., H. Pinheiro, T. Degner, and G. Arnold. 2010. Robust controller for DFIGs of grid-connected wind turbines. IEEE Transactions on Industrial Electronics 58 (9):4023–38. doi:10.1109/TIE.2010.2098630.
   Web of Science ®Google Scholar
• Dahbi, A., A. Reama, M. Hamouda, N. Nait-Said, and M. S. Nait-Said. 2019. Control and study of a real wind turbine. Computers & Electrical Engineering 80:1–16. doi:10.1016/j.compeleceng.2019.106492.
   Web of Science ®Google Scholar
• Ding, S., J. Wang, and W. X. Zheng. 2015. Second-order sliding mode control for nonlinear uncertain systems bounded by positive functions. IEEE Transactions on Industrial Electronics 62 (9):5899–909. doi:10.1109/TIE.2015.2448064.
   Web of Science ®Google Scholar
• El Mehdi, A. S. A., and M. Abid. 2015. Fuzzy sliding mode control applied to a doubly fed induction generator for wind turbines. Turkish Journal of Electrical Engineering and Computer Sciences 23 (6):1673–86. doi:10.3906/elk-1404-64.
   Web of Science ®Google Scholar
• Evangelista, C., F. Valenciaga, and P. Puleston. 2013. Active and reactive power control for wind turbine based on a MIMO 2-sliding mode algorithm with variable gains. IEEE Transactions on Energy Conversion 28 (3):682–89. doi:10.1109/TEC.2013.2272244.
   Web of Science ®Google Scholar
• Fridman, L., and A. Levant. 1996. Higher order sliding modes as a natural phenomenon in control theory. Berlin, Heidelberg: Springer-Verlag. 107–33. doi:10.1007/BFb0027563.
   Google Scholar
• Fu, C., and W. Tan. 2021. Analysis and tuning of reduced-order active disturbance rejection control. Journal of the Franklin Institute 358 (1):339–62. doi:10.1016/j.jfranklin.2020.10.017.
   Web of Science ®Google Scholar
• Gadoue, S. M., D. Giaouris, and J. W. Finch. 2010. MRAS sensorless vector control of an induction motor using new sliding-mode and fuzzy-logic adaptation mechanisms. IEEE Transactions on Energy Conversion 25 (2):394–402. doi:10.1109/TEC.2009.2036445.
   Web of Science ®Google Scholar
• Gao, Z. 2015. Active disturbance rejection control for nonlinear fractional-order systems. International Journal of Robust and Nonlinear Control 26 (4):876–92. doi:10.1002/rnc.3344.
   Web of Science ®Google Scholar
• Gebru, F. M., B. Khan, and H. H. Alhelou. 2020. Analyzing low voltage ride through capability of doubly fed induction generator based wind turbine. Computers & Electrical Engineering 86 (3):1–19. doi:10.1016/j.compeleceng.2020.106727.
   Google Scholar
• Guo, B. Z., and Z. L. Zhao. 2016. Active disturbance rejection control for nonlinear systems: An introduction. SPi Global, Chennai, India: John Wiley & Sons. doi:10.1002/9781119239932.ch2.
   Google Scholar
• Han, J. 2009. From PID to auto disturbances rejection control. IEEE Transactions on Industrial Electronics 56 (3):900–06. doi:10.1109/TIE.2008.2011621.
   Web of Science ®Google Scholar
• Huang, Y. C., and J. Q. Han. 1998. Continuous-time system identification with the extended states observer. Control and Decision 4:381–84.
   Google Scholar
• Kassem, A. M., K. M. Hasaneen, and A. Yousef. 2013. Dynamic modeling and robust power control of DFIG driven by wind turbine at infinite grid. International Journal of Electrical Power & Energy Systems 44 (1):375–82. doi:10.1016/j.ijepes.2011.06.038.
   Web of Science ®Google Scholar
• Khalil, H. K. 2002. Nonlinear systems. Third edition. Englewood ed. Cliffs, NJ: Prentice-Hall.
   Google Scholar
• Kimathi, S. M. 2018. Design of an online adaptive controller for active disturbance rejection in a fixed wing UAV using reinforcement learning and differential games. M.Sc. dissertation, Jomo Kenyatta University of Agriculture and Technology. http://ir.jkuat.ac.ke/bitstream/handle/123456789/4543/Thesis.pdf.
   Google Scholar
• Laghridat, H., A. Essadki, M. Annoukoubi, and T. Nasser. 2020. A novel adaptive active disturbance rejection control strategy to improve the stability and robustness for a wind turbine using a doubly fed induction generator. Journal of Electrical and Computer Engineering 8:1–14. doi:10.1155/2020/9847628.
   Web of Science ®Google Scholar
• Laghrouche, S., F. Plestan, and A. Glumineau. 2007. Higher order sliding mode control based on integral sliding mode. Automatica Elsevier 43 (3):531–37. doi:10.1016/j.automatica.2006.09.017.
   Web of Science ®Google Scholar
• Levant, A., and L. V. Levantovsky. 1993. Sliding order and sliding accuracy in sliding mode control. International Journal of Control 58 (6):1247–63. doi:10.1080/00207179308923053.
   Web of Science ®Google Scholar
• Levant, A. 2007. Principles of 2-sliding mode design. Automatica Elsevier 43 (4):576–86. doi:10.1016/j.automatica.2006.10.008.
   Web of Science ®Google Scholar
• Lin, W. M., C. M. Hong, and F. S. Cheng. 2010. Fuzzy neural network output maximization control for sensorless wind energy conversion system. Energy Elsevier 35 (2):592–601. doi:10.1016/j.energy.2009.10.030.
   Google Scholar
• Liu, X., and X. Kong. 2013. Nonlinear model predictive control for DFIG-based wind power generation. IEEE Transactions on Automation Science and Engineering 11 (4):1046–55. doi:10.1109/TASE.2013.2284066.
   Web of Science ®Google Scholar
• Luo, H., H. Cheng, and J. Wang. 2015. A cascade linear active disturbance rejection controller for vector control system of PMSM. Proceedings of 3rd International Conference on Mechatronics, Robotics and Automation, Shenzhen, China, 1076–82. doi:10.2991/icmra-15.2015.208.
   Google Scholar
• Mauricio, J. M., A. E. Leon, A. Gomez-Exposito, and J. A. Solsona. 2008. An adaptive nonlinear controller for dfim-based wind energy conversion systems. IEEE Transactions on Energy Conversion 23 (4):1025–35. doi:10.1109/TEC.2008.2001441.
   Web of Science ®Google Scholar
• Melicio, R., V. M. F. Mendes, and J. P. S. Catalao. 2011. Comparative study of power converter topologies and control strategies for the harmonic performance of variable-speed wind turbine generator systems. Energy Elsevier 36 (1):520–29. doi:10.1016/j.energy.2010.10.012.
   Google Scholar
• Moradi, H., and G. Vossoughi. 2015. Robust control of the variable speed wind turbines in the presence of uncertainties: A comparison between H∞ and PID controllers. Energy Elsevier 90 (2):1508–21. doi:10.1016/j.energy.2015.06.100.
   Google Scholar
• Morren, J., and S. W. H. de Haan. 2007. Short-circuit current of wind turbines with doubly fed induction generator. IEEE Transactions on Energy Conversion 22 (1):174–80. doi:10.1109/TEC.2006.889615.
   Web of Science ®Google Scholar
• Munteanu, I., N. A. Cutululis, A. I. Bratcu, and E. Ceanga. 2005. Optimization of variable speed wind power systems based on a LQG approach. Control Engineering Practice Elsevier 13 (7):903–12. doi:10.1016/j.conengprac.2004.10.013.
   Web of Science ®Google Scholar
• Pan, C. T., and Y. L. Juan. 2010. A novel sensorless MPPT controller for a high-efficiency microscale wind power generation system. IEEE Transactions on Energy Conversion 25 (1):207–16. doi:10.1109/TEC.2009.2032604.
   Web of Science ®Google Scholar
• Pande, V. N., U. M. Mate, and S. Kurode. 2013. Discrete sliding mode control strategy for direct real and reactive power regulation of wind driven DFIG. Electric Power Systems Research Elsevier 100:73–81. doi:10.1016/j.epsr.2013.03.001.
   Web of Science ®Google Scholar
• Peng, N., Y. Bai, H. Luo, and J. Bai. 2013. Artillery position control through auto disturbance rejection controller based-on fuzzy control. Proceedings of 5th International Conference on Intelligent Human-Machine Systems and Cybernetics IEEE, Hangzhou, China, 496–99. doi:10.1109/IHMSC.2013.124.
   Google Scholar
• Petras, I. 2008. Stability of fractional-order systems with rational orders. Fractional Calculation Application Analysis 10(3): 1–25.
   Google Scholar
• Pichan, M., H. Rastegar, and M. Monfared. 2013. Two fuzzy-based direct power control strategies for doubly-fed induction generators in wind energy conversion systems. Energy Elsevier 51:154–62. doi:10.1016/j.energy.2012.12.047.
   Google Scholar
• Quari, K., T. Rekioua, and M. Ouhrouche. 2014. Real time simulation of nonlinear generalized predictive control for wind energy conversion system with nonlinear observer. ISA Transactions Elsevier 53 (1):76–84. doi:10.1016/j.isatra.2013.08.004.
   PubMed Web of Science ®Google Scholar
• Seker, M., E. Zergeroglu, and E. Tatlicioglu. 2013. Non-linear control of variable-speed wind turbines with permanent magnet synchronous generators: A robust backstepping approach. International Journal of Systems Science 47 (2):1–13. doi:10.1080/00207721.2013.834087.
   Google Scholar
• Sguarezi Filho, A. J., M. E. Oliveira Filho, and E. Ruppert. 2011. A predictive power control for wind energy. IEEE Transactions on Sustainable Energy 2 (1):97–105. doi:10.1109/TSTE.2010.2088408.
   Web of Science ®Google Scholar
• Song, J., K. Gao, L. Wang, and E. Yang. 2016. Comparison of linear and nonlinear active disturbance rejection control method for hypersonic vehicle. Proceedings of 35th Chinese Control Conference CCC IEEE, Chengdu, China, 1–6. doi:10.1109/ChiCC.2016.7555064.
   Google Scholar
• Struggl, S., V. Berbyuk, and H. Johansson. 2015. Review on wind turbines with focus on drive train system dynamics. Wind Energy 18:567–90. doi:10.1002/we.1721.
   Web of Science ®Google Scholar
• Sun, L., D. Li, and Z. Gao. 2016. Combined feed forward and model-assisted active disturbance rejection control for non-minimum phase system. ISA Transactions Elsevier 64 (4):24–33. doi:10.1016/j.isatra.2016.04.020.
   PubMed Web of Science ®Google Scholar
• Surinkaew, T., and I. Ngamroo. 2014. Coordinated robust control of DFIG wind turbine and PSS for stabilization of power oscillations considering system uncertainties. IEEE Transactions on Sustainable Energy 5 (3):823–33. doi:10.1109/TSTE.2014.2308358.
   Web of Science ®Google Scholar
• Taveiros, F. E. V., L. S. Barros, and F. B. Costa. 2015. Back-to-back converter state-feedback control of DFIG (doubly-fed induction generator)-based wind turbines. Energy Elsevier 89:896–906. doi:10.1016/j.energy.2015.06.027.
   Google Scholar
• Tohidi, A., H. Hajieghrary, and M. Ani Hsieh. 2016. Adaptive disturbance rejection control scheme for DFIG-based wind turbine: Theory and experiments. IEEE Transactions on Industry Applications 52 (3):2006–15. doi:10.1109/TIA.2016.2521354.
   Web of Science ®Google Scholar
• Utkin, V., and H. Lee. 2006. Chattering problem in sliding mode control systems. Proceedings of International Workshop on Variable Structure Systems IEEE, Alghero, Sardinia, 346–50. doi:10.1109/VSS.2006.1644542.
   Google Scholar
• Wang, J., L. He, and M. Sun. 2010. Application of active disturbance rejection control to integrated flight-propulsion control. Proceedings of Chinese Control and Decision Conference, Xuzhou, China, 2565–69. doi:10.1109/CCDC.2010.5498776.
   Google Scholar
• Wang, Y. W., K. X. Xing, and J. Ma. 2017. Implementation and design of active disturbance rejection control for the linear inverted pendulum. Control Engineering of China 24 (4):711–15.
   Google Scholar
• Wang, F., R. J. Wang, and E. H. Liu. 2019. Analysis and tuning for active disturbance rejection control. Mathematical Problems in Engineering 1:1–11. doi:10.1155/2019/9641723.
   Google Scholar
• Wang, Y., Z. Chen, M. Sun, and Q. Sun. 2022. Design and stability analysis of a generalized reduced-order active disturbance rejection controller. Science China Technological Sciences 65:361–74. doi:10.1007/s11431-020-1803-4.
   Web of Science ®Google Scholar
• Wessels, C., and F. W. Fuchs. 2010. Fault ride through of DFIG wind turbines during symmetrical voltage dip with crowbar or stator current feedback solution. Proceedings of Energy Conversion Congress and Exposition IEEE, Atlanta, GA, USA, 2771–77. doi:10.1109/ECCE.2010.5618076.
   Google Scholar
• Wu, Z. Q., Y. Yang, and C. H. Xu. 2015. Adaptive fault diagnosis and active tolerant control for wind energy conversion system. International Journal of Control, Automation and Systems 13 (1):120–25. doi:10.1007/s12555-013-0148-z.
   Web of Science ®Google Scholar
• Xu, L., and P. Cartwright. 2006. Direct active and reactive power control of DFIG for wind energy generation. IEEE Transactions on Energy Conversion 21 (3):750–58. doi:10.1109/TEC.2006.875472.
   Web of Science ®Google Scholar
• Yang, B., L. Jian, L. Wang, W. Yao, and Q. H. Wu. 2016. Nonlinear maximum power point tracking control and modal analysis of DFIG based wind turbine. International Journal of Electrical Power & Energy Systems Elsevier 74:429–36. doi:10.1016/j.ijepes.2015.07.036.
   Web of Science ®Google Scholar
• Yang, X., J. Cui, and D. Lao. 2016. Input shaping enhanced active disturbance rejection control for a twin rotor multi-input multi-output system (TRMS). ISA Transactions Elsevier 62:287–98. doi:10.1016/j.isatra.2016.02.001.
   PubMed Web of Science ®Google Scholar
• Yu, Y., H. Wang, X. Shao, and Y. Huang. 2016. The attitude control of UAV in carrier landing based on ADRC. Proceedings of Chinese Guidance, Navigation and Control Conference CGNCC IEEE, Nanjing, China, 832–37. doi:10.1109/CGNCC.2016.7828893.
   Google Scholar
• Zhang, R., and J. Q. Han. 2000. Parameter identification by model compensation auto disturbance rejection controller. Control Theory & Applications 17 (1):79–81.
   Google Scholar
• Zhao, S., and Z. Gao. 2010. Active disturbance rejection control for non-minimum phase systems. Proceedings of the 29th Chinese Control Conference, Beijing, China, 6066–70.
   Google Scholar
• Zhou, Z., H. Peng, B. Liu, W. Wang, G. Niu, and C. Liu. 2021. Power decoupling control of DFIG rotor-side PWM converter based on auto-disturbance rejection control. Wind Energy 1–13. doi:10.1002/we.2662.
   Web of Science ®Google Scholar