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Volume 8 Issue 3
Mar.  2021

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2021  >  8(3): 690-700
Saber Abrazeh, Ahmad Parvaresh, Saeid-Reza Mohseni, Meisam Jahanshahi Zeitouni, Meysam Gheisarnejad and Mohammad Hassan Khooban, "Nonsingular Terminal Sliding Mode Control With Ultra-Local Model and Single Input Interval Type-2 Fuzzy Logic Control for Pitch Control of Wind Turbines," IEEE/CAA J. Autom. Sinica, vol. 8, no. 3, pp. 690-700, Mar. 2021. doi: 10.1109/JAS.2021.1003889
Citation: Saber Abrazeh, Ahmad Parvaresh, Saeid-Reza Mohseni, Meisam Jahanshahi Zeitouni, Meysam Gheisarnejad and Mohammad Hassan Khooban, "Nonsingular Terminal Sliding Mode Control With Ultra-Local Model and Single Input Interval Type-2 Fuzzy Logic Control for Pitch Control of Wind Turbines," IEEE/CAA J. Autom. Sinica, vol. 8, no. 3, pp. 690-700, Mar. 2021. doi: 10.1109/JAS.2021.1003889
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Nonsingular Terminal Sliding Mode Control With Ultra-Local Model and Single Input Interval Type-2 Fuzzy Logic Control for Pitch Control of Wind Turbines

doi: 10.1109/JAS.2021.1003889
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    Abstract
  • As wind energy is becoming one of the fastest-growing renewable energy resources, controlling large-scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties. The main goal of the current work is to propose an intelligent control of the wind turbine system without the need for model identification. For this purpose, a novel model-independent nonsingular terminal sliding-mode control (MINTSMC) using the basic principles of the ultra-local model (ULM) and combined with the single input interval type-2 fuzzy logic control (SIT2-FLC) is developed for non-linear wind turbine pitch angle control. In the suggested control framework, the MINTSMC scheme is designed to regulate the wind turbine speed rotor, and a sliding-mode (SM) observer is adopted to estimate the unknown phenomena of the ULM. The auxiliary SIT2-FLC is added in the model-independent control structure to improve the rotor speed regulation and compensate for the SM observation estimation error. Extensive examinations and comparative analyses were made using a real-time software-in-the-loop (RT-SiL) based on the dSPACE 1202 board to appraise the efficiency and applicability of the suggested model-independent scheme in a real-time testbed.

     

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    • References(41)
  • [1]
    M. Gheisarnejad, H. Mohammadi-Moghadam, J. Boudjadar, and M. H. Khooban, “Active power sharing and frequency recovery control in an islanded microgrid with nonlinear load and nondispatchable DG,” IEEE Syst. J., vol. 14, no. 1, pp. 1058–1068, Mar. 2020. doi: 10.1109/JSYST.2019.2927112
    [2]
    T. L. Van, T. H. Nguyen, and D. C. Lee, “Advanced pitch angle control based on fuzzy logic for variable-speed wind turbine systems,” IEEE Trans. Energy Convers., vol. 30, no. 2, pp. 578–587, Jun. 2015. doi: 10.1109/TEC.2014.2379293
    [3]
    C. J. Liu, D. H. Xu, N. Zhu, F. Blaabjerg, and M. Chen, “DC-voltage fluctuation elimination through a DC-capacitor current control for DFIG converters under unbalanced grid voltage conditions,” IEEE Trans. Power Electron., vol. 28, no. 7, pp. 3206–3218, Jul. 2013. doi: 10.1109/TPEL.2012.2223829
    [4]
    M. Andalibi and F. Shabaninia, “Reactive power control technique for variable speed wind turbines during grid faults considering their reactive power capability,” Master Thesis, Aalborg University, Denmark, 2010.
    [5]
    B. Beltran, M. El Hachemi Benbouzid, and T. Ahmed-Ali, “Second-order sliding mode control of a doubly fed induction generator driven wind turbine,” IEEE Trans. Energy Convers., vol. 27, no. 2, pp. 261–269, Jun. 2012. doi: 10.1109/TEC.2011.2181515
    [6]
    A. Parvaresh, S. Abrazeh, S. R. Mohseni, M. J. Zeitouni, M. Gheisarnejad, and M. H. Khooban, “A novel deep learning backstepping controller-based digital twins technology for pitch angle control of variable speed wind turbine,” Designs, vol. 4, no. 2, pp. 15, Jun. 2020. doi: 10.3390/designs4020015
    [7]
    M. J. Zeitouni, A. Parvaresh, S. Abrazeh, S. R. Mohseni, M. Gheisarnejad, and M. H. Khooban, “Digital twins-assisted design of next-generation advanced controllers for power systems and electronics: Wind turbine as a case study,” Inventions, vol. 5, no. 2, pp. 19, May 2020. doi: 10.3390/inventions5020019
    [8]
    Y. X. Ren, L. Y. Li, J. Brindley, and L. Jiang, “Nonlinear PI control for variable pitch wind turbine,” Control Eng. Pract., vol. 50, pp. 84–94, May 2016. doi: 10.1016/j.conengprac.2016.02.004
    [9]
    A. Elmansouri, J. El Mhamdi, A. Boualouch, and A. Aamoud, “MPPT control of DFIG in WECS using back-stepping controller,” in Proc. 3rd Int. Renewable and Sustainable Energy Conf., Marrakech, Morocco, 2015, pp. 1–7.
    [10]
    D. Kim and D. Lee, “Hierarchical fault-tolerant control using model predictive control for wind turbine pitch actuator faults,” Energies, vol. 12, no. 16, pp. 3097, Aug. 2019. doi: 10.3390/en12163097
    [11]
    Y. Yuan and J. Tang, “Adaptive pitch control of wind turbine for load mitigation under structural uncertainties,” Renew. Energy, vol. 105, pp. 483–494, May 2017. doi: 10.1016/j.renene.2016.12.068
    [12]
    K. A. Naik and C. P. Gupta, “Output power smoothing and voltage regulation of a fixed speed wind generator in the partial load region using STATCOM and a pitch angle controller,” Energies, vol. 11, no. 1, pp. 58, Jan. 2018.
    [13]
    G. Abdalrahman, W. Melek, and F. S. Lien, “Pitch angle control for a small-scale Darrieus vertical axis wind turbine with straight blades (H-Type VAWT),” Renew. Energy, vol. 114, pp. 1353–1362, Dec. 2017. doi: 10.1016/j.renene.2017.07.068
    [14]
    E. B. Muhando, T. Senjyu, A. Uehara, and T. Funabashi, “Gain-scheduled H∞ control for WECS via LMI techniques and parametrically dependent feedback Part Ⅱ: Controller design and implementation,” IEEE Trans. Ind. Electron., vol. 58, no. 1, pp. 57–65, Jan. 2011. doi: 10.1109/TIE.2010.2045414
    [15]
    B. Boukhezzar and H. Siguerdidjane, “Comparison between linear and nonlinear control strategies for variable speed wind turbines,” Control Eng. Pract., vol. 18, no. 12, pp. 1357–1368, Dec. 2010. doi: 10.1016/j.conengprac.2010.06.010
    [16]
    L. Shang and J. B. Hu, “Sliding-mode-based direct power control of grid-connected wind-turbine-driven doubly fed induction generators under unbalanced grid voltage conditions,” IEEE Trans. Energy Convers., vol. 27, no. 2, pp. 362–373, Jun. 2012. doi: 10.1109/TEC.2011.2180389
    [17]
    T. Elmokadem, M. Zribi, and K. Youcef-Toumi, “Terminal sliding mode control for the trajectory tracking of underactuated Autonomous Underwater Vehicles,” Ocean Eng., vol. 129, pp. 613–625, Jan. 2017. doi: 10.1016/j.oceaneng.2016.10.032
    [18]
    Y. Feng, X. H. Yu, and Z. H. Man, “Non-singular terminal sliding mode control of rigid manipulators,” Automatica, vol. 38, no. 12, pp. 2159–2167, Dec. 2002. doi: 10.1016/S0005-1098(02)00147-4
    [19]
    Z. Zuo, “Non-singular fixed-time terminal sliding mode control of non-linear systems,” IET Control Theory Appl., vol. 9, no. 4, pp. 545–552, Feb. 2015. doi: 10.1049/iet-cta.2014.0202
    [20]
    H. Moradi and G. Vossoughi, “Robust control of the variable speed wind turbines in the presence of uncertainties: A comparison between H∞ and PID controllers,” Energy, vol. 90, pp. 1508–1521, Oct. 2015. doi: 10.1016/j.energy.2015.06.100
    [21]
    J. B. Qiu, K. K. Sun, T. Wang, and H. J. Gao, “Observer-based fuzzy adaptive event-triggered control for pure-feedback nonlinear systems with prescribed performance,” IEEE Trans. Fuzzy Syst., vol. 27, no. 11, pp. 2152–2162, Nov. 2019. doi: 10.1109/TFUZZ.2019.2895560
    [22]
    P. H. Du, Y. N. Pan, H. Y. Li, and H. K. Lam, “Nonsingular finite-time event-triggered fuzzy control for large-scale nonlinear systems,” IEEE Trans. Fuzzy Syst., DOI: 10.1109/TFUZZ.2020.2992632, 2020.
    [23]
    J. B. Qiu, K. K. Sun, I. J. Rudas, and H. J. Gao, “Command filter-based adaptive NN control for MIMO nonlinear systems with full-state constraints and actuator hysteresis,” IEEE Trans. Cybernet., vol. 50, no. 7, pp. 2905–2915, Jul. 2020. doi: 10.1109/TCYB.2019.2944761
    [24]
    D. R. Liu, Y. Z. Huang, D. Wang, and Q. L. Wei, “Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming,” Int. J. Control, vol. 86, no. 9, pp. 1554–1566, May 2013. doi: 10.1080/00207179.2013.790562
    [25]
    B. Beltran, T. Ahmed-Ali, and M. El Hachemi Benbouzid, “High-order sliding-mode control of variable-speed wind turbines,” IEEE Trans. Ind. Electron., vol. 56, no. 9, pp. 3314–3321, Sept. 2009. doi: 10.1109/TIE.2008.2006949
    [26]
    J. T. Agee, S. Kizir, and Z. Bingul, “Intelligent proportional-integral (iPI) control of a single link flexible joint manipulator,” J. Vib. Control, vol. 21, no. 11, pp. 2273–2288, Aug. 2015. doi: 10.1177/1077546313510729
    [27]
    K. H. Zhao, T. H. Yin, C. F. Zhang, J. He, X. F. Li, Y. Chen, R. R. Zhou, and A. J. Leng, “Robust model-free nonsingular terminal sliding mode control for PMSM demagnetization fault,” IEEE Access, vol. 7, pp. 15737–15748, Jan. 2019. doi: 10.1109/ACCESS.2019.2895512
    [28]
    M. Mosayebi, M. Gheisarnejad, and M. H. Khooban, “An intelligent type-2 fuzzy stabilization of Multi-DC Nano power grids,” IEEE Trans. Emerg. Top. Comput. Intell., DOI: 10.1109/TETCI.2020.2977676, 2020.
    [29]
    F. H. Zhou and J. Liu, “Pitch controller design of wind turbine based on nonlinear PI/PD control,” Shock Vib., vol. 2018, pp. 7859510, Oct. 2018.
    [30]
    H. Abouaissa and S. Chouraqui, “On the control of robot manipulator: A model-free approach,” J. Comput. Sci., vol. 31, pp. 6–16, Feb. 2019. doi: 10.1016/j.jocs.2018.12.011
    [31]
    C. F. Zhang, G. P. Wu, J. He, and K. H. Zhao, “Sliding observer-based demagnetization fault-tolerant control in permanent magnet synchronous motors,” J. Eng., vol. 2017, no. 6, pp. 175–183, Jun. 2017.
    [32]
    M. H. Khooban and M. Gheisarnejad, “A novel deep reinforcement learning controller based type-Ⅱ fuzzy system: Frequency regulation in microgrids,” IEEE Trans. Emerg. Top. Comput. Intell., DOI: 10.1109/TETCI.2020.2964886, 2020.
    [33]
    R. Heydari, M. Gheisarnejad, M. H. Khooban, T. Dragicevic, and F. Blaabjerg, “Robust and fast voltage-source-converter (VSC) control for naval shipboard microgrids,” IEEE Trans. Power Electron., vol. 34, no. 9, pp. 8299–8303, Sept. 2019. doi: 10.1109/TPEL.2019.2896244
    [34]
    A. Sarabakha, C. H. Fu, E. Kayacan, and T. Kumbasar, “Type-2 fuzzy logic controllers made even simpler: From design to deployment for UAVs,” IEEE Trans. Ind. Electron., vol. 65, no. 6, pp. 5069–5077, Jun. 2018. doi: 10.1109/TIE.2017.2767546
    [35]
    M. Mehndiratta, E. Kayacan, and T. Kumbasar, “Design and experimental validation of single input type-2 fuzzy PID controllers as applied to 3 DOF helicopter testbed,” in Proc. IEEE Int. Conf. Fuzzy Systems, Vancouver, BC, Canada, 2016, pp. 1584–1591.
    [36]
    T. Kumbasar, “Robust stability analysis and systematic design of single-input interval type-2 fuzzy logic controllers,” IEEE Trans. Fuzzy Syst., vol. 24, no. 3, pp. 675–694, Jun. 2016. doi: 10.1109/TFUZZ.2015.2471805
    [37]
    M. Gheisarnejad, J. Boudjadar, and M. H. Khooban, “A new adaptive type-Ⅱ fuzzy-based deep reinforcement learning control: Fuel cell air-feed sensors control,” IEEE Sens. J., vol. 19, no. 20, pp. 9081–9089, Oct. 2019. doi: 10.1109/JSEN.2019.2924726
    [38]
    Y. Z. Wang, Q. B. Jin, and R. D. Zhang, “Improved fuzzy PID controller design using predictive functional control structure,” ISA Trans., vol. 71, pp. 354–363, Nov. 2017. doi: 10.1016/j.isatra.2017.09.005
    [39]
    A. Kumar and V. Kumar, “A novel interval type-2 fractional order fuzzy PID controller: Design, performance evaluation, and its optimal time domain tuning,” ISA Trans., vol. 68, pp. 251–275, May 2017. doi: 10.1016/j.isatra.2017.03.022
    [40]
    R. E. Precup and M. L. Tomescu, “Stable fuzzy logic control of a general class of chaotic systems,” Neural Comput. Appl., vol. 26, pp. 541–550, Apr. 2015. doi: 10.1007/s00521-014-1644-7
    [41]
    Y. N. Pan, P. H. Du, H. Xue, and H. K. Lam, “Singularity-free fixed-time fuzzy control for robotic systems with user-defined performance,” IEEE Trans. Fuzzy Syst., DOI: 10.1109/TFUZZ.2020.2999746, 2020.
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    Highlights

    • A novel nonsingular terminal sliding mode control combined with the single input interval type-2 fuzzy logic control (SIT2-FLC) is developed for the stabilization of a typical wind turbine system.
    • Extensive examinations are conducted based on software-in-the-loop (RT-SiL) to demonstrate the efficiency and applicability of the suggested scheme in a real-time testbed.
    • The performance of the suggested controller under sudden and stochastic changes of wind speed is investigated.

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