Neuro-adaptive backstepping integral sliding mode control design for nonlinear wind energy conversion system

Neuro-adaptive backstepping integral sliding mode control design for nonlinear wind energy conversion system

The electrical power extracted from a wind energy conversion system (WECS) tends to be inconsistent due to the intermittent nature of the wind. This issue is addressed by formulating a maximum power point tracking (MPPT) control strategy that optimizes the power extraction from the WECS under a wide range of wind speed profiles. This research article focuses on the formulation of a nonlinear neuro-adaptive backstepping integral sliding mode control (NABISMC) based MPPT strategy for a standalone, variable speed, fixed-pitch WECS equipped with a permanent magnet synchronous generator (PMSG). The proposed paradigm is a hybrid of the conventional backstepping and the integral sliding mode control (ISMC) based MPPT schemes. The effectiveness of the control strategy devised is guaranteed through numerical simulations carried out in Matlab/Simulink for a 3 kW PMSG-WECS under a stochastic wind speed profile. Further validation is guaranteed by giving a detailed performance comparison analysis of the proposed MPPT control strategy with the conventional feedback linearization control (FBLC), proportional integral derivative (PID) control, sliding mode control (SMC), and standard neuro-adaptive integral sliding mode control (NAISMC) based MPPT strategies, where the proposed strategy is found superior to all the stated strategies in terms of offering more accurate MPPT, lower steady state error, faster dynamic response and lesser chattering.

___

  • [1] Hamatwi E, Davidson IE, Gitau MN. Rotor speed control of a direct-driven permanent magnet synchronous generator-based wind turbine using phase-lag compensators to optimize wind power extraction. Journal of Control Science Engineering 2017; 1: 1-17. doi: 10.1155/2017/6375680
  • [2] Tahir K, Belfedal C, Allaoui T, Denai M, Doumi, M. A new sliding mode control strategy for variable-speed wind turbine power maximization. International Transactions on Electrical Energy Systems 2018; 28 (4): e2513. doi: 10.1002/etep.2513
  • [3] Yazici İ, Yaylaci EK. Maximum power point tracking for the permanent magnet synchronous generator-based WECS by using the discrete-time integral sliding mode controller with a chattering-free reaching law. IET Power Electronics 2017; 10 (13): 1751-1758. doi: 10.1049/iet-pel.2017.0232
  • [4] Asri A, Mihoub Y, Hassaine S, Logerais PO, Allaoui T. Intelligent maximum power tracking control of a PMSG wind energy conversion system. Asian Journal of Control 2019; 21 (4): 1980-1990. doi: 10.1002/asjc.2090
  • [5] Yaramasu V, Dekka A, Durán MJ, Kouro S, Wu B. PMSG-based wind energy conversion systems: survey on power converters and controls. IET Electric Power Applications 2017; 11 (6): 956-968. doi: 10.1049/iet-epa.2016.0799
  • [6] Soliman MA, Hasanien HM, Azazi HZ, El-kholy EE, Mahmoud SA. Linear-quadratic regulator algorithm-based cascaded control scheme for performance enhancement of a variable-speed wind energy conversion system. Arabian Journal for Science and Engineering 2019; 44 (3): 2281-2293. doi: 10.1007/s13369-018-3433-6
  • [7] Shtessel Y, Edwards C, Fridman L, Levant A. Sliding Mode Control and Observation. Birkhäuser, NY, USA: Springer, 2014.
  • [8] Young KD, Utkin VI, Ozguner U. A control engineer’s guide to sliding mode control. IEEE Transactions on Control Systems Technology 1999; 7 (3): 328-342. doi: 10.1109/87.761053
  • [9] Coban R. Adaptive backstepping sliding mode control with tuning functions for nonlinear uncertain systems. International Journal of Systems Science 2019; 50 (8): 1517-1529. doi: 10.1080/00207721.2019.1615571
  • 10] Coban R. Dynamical adaptive integral backstepping variable structure controller design for uncertain systems and experimental application. International Journal of Robust and Nonlinear Control 2017; 27 (18): 4522-4540. doi: 10.1002/rnc.3810
  • [11] Aksu IO, Coban R. Sliding mode PI control with backstepping approach for MIMO nonlinear cross‐coupled tank systems. International Journal of Robust and Nonlinear Control 2019; 29 (6): 1854-1871. doi: 10.1002/rnc.4469
  • [12] Utkin V, Sh J. Integral sliding mode in systems operating under uncertainty conditions. In: Proceed- ings of 35th IEEE Conference on Decision and Control; New York, NY, USA; 1996. pp. 4591-4596. doi: 10.1109/CDC.1996.577594
  • [13] Xia, C, Wang X, Li S, Chen X. Improved integral sliding mode control methods for speed control of PMSM system. International Journal of Innovative Computing, Information and Control 2006; 7: 1971-1982.
  • [14] Wang J, Bo D, Ma X, Zhang Y, Li Z et al. Adaptive back-stepping control for a permanent magnet synchronous generator wind energy conversion system. International Journal of Hydrogen Energy 2019; 44 (5): 3240-3249. doi: 10.1016/j.ijhydene.2018.12.023
  • [15] Errami Y, Obbadi A, Sahnoun S, Benhmida M, Ouassaid M et al. Design of a nonlinear backstepping control strategy of grid interconnected wind power system based PMSG. In: AIP Conference Proceedings; Beirut, Lebanon; 2016. pp. 030053.
  • [16] Krstić M, Kanellakopoulos I, Kokotović, PV. Nonlinear and Adaptive Control Design. USA: John Wiley & Sons Inc., 1995.
  • [17] Krstić M, Smyshlyaev A. Boundary Control of PDEs: A Course on Backstepping Designs. Philadelphia, PA, USA: Siam (Society for Industrial and Applied Mathematics), 2008.
  • [18] Cheikh R, Menacer A, Chrifi-Alaoui L, Drid S. Robust nonlinear control via feedback linearization and Lyapunov theory for permanent magnet synchronous generator-based wind energy conversion system. Frontiers in Energy 2018; 1: 1-12. doi: 10.1007/s11708-018-0537-3
  • [19] Subramaniam R, Joo YH. Passivity-based fuzzy ISMC for wind energy conversion systems with PMSG. IEEE Transactions on Systems, Man, and Cybernetics: Systems 2019; 1: 1-10. doi: 10.1109/TSMC.2019.2930743
  • [20] Heshmatian S, Khaburi DA, Khosravi Mahyar, Kazemi A. A control scheme for maximizing the delivered power to the load in a standalone wind energy conversion system. Turkish Journal of Electrical Engineering and Computer Sciences 2019; 27 (4): 2998-3014. doi: 10.3906/elk-1809-166
  • [21] Munteanu I, Bratcu AI, Cutululis NA, Ceanga E. Optimal Control of Wind Energy Systems: Towards a Global Approach. London, UK: Springer-Verlag, 2008. doi: 10.1007/978-1-84800-080-3
  • [22] Cutululis NA, Ceanga E, Hansen AD, Sørensen P. Robust multi-model control of an autonomous wind power system. Wind Energy 2006; 9 (5): 399-419. doi: 10.1002/we.194
  • [23] Mat-Noh M, Arshad MR, Mohd-Mokhtar R, Khan Q. Back-stepping integral sliding mode control (BISMC) appli- cation in a nonlinear autonomous underwater glider. In: IEEE 7th International Conference on Underwater System Technology: Theory and Applications (USYS); Kuala Lumpur, Malaysia; 2017. pp. 1-6.
  • [24] Khan Q, Bhatti AI, Iqbal S, Iqbal M. Dynamic integral sliding mode for MIMO uncertain nonlinear systems. International Journal of Control, Automation, and Systems 2011; 9 (1): 151-160. doi: 10.1007/s12555-011-0120-8
  • [25] Duman S, Yörükeren N, Altaş İH. Gravitational search algorithm for determining controller parameters in an automatic voltage regulator system. Turkish Journal of Electrical Engineering and Computer Sciences 2016; 24 (4): 2387-2400. doi: 10.3906/elk-1404-14
  • [26] Ali K, Khan Q, Ullah S, Khan I, Khan L. Nonlinear robust integral backstepping based MPPT control for stand- alone photovoltaic system. PLoS One 2020; 15 (5): e0231749. doi: 10.1371/journal.pone.0231749
  • [27] Sami I, Ullah S, Ali Z, Ullah N, Ro JS. A super twisting fractional order terminal sliding mode control for DFIG- based wind energy conversion system. Energies 2020; 13 (9): 2158. doi: 10.3390/en13092158
Turkish Journal of Electrical Engineering and Computer Sciences-Cover
  • ISSN: 1300-0632
  • Yayın Aralığı: Yılda 6 Sayı
  • Yayıncı: TÜBİTAK
Sayıdaki Diğer Makaleler

Sliding mode PLL-PDM controller for induction heating system

Harun ÖZBAY, Akif KARAFİL, Selim ÖNCÜ

An adversarial framework for open-set human action recognition using skeleton data

Özge ÖZTİMUR KARADAĞ

Dynamic distributed trust management scheme for the Internet of Things

Syed Wasif Abbas HAMDAN, Abdul Waheed KHAN, Naima ILTAF, Javed Iqbal BANGASH, Yawar Abbas BANGASH, Asfandyar KHAN

Development of majority vote ensemble feature selection algorithm augmented with rank allocation to enhance Turkish text categorization

Akın ÖZÇİFT, Emin BORANDAĞ, Yeşim KAYGUSUZ

Turkish sign language recognition based on multistream data fusion

Hüseyin POLAT, Cemil GÜNDÜZ

A nonlinear disturbance observer scheme for discrete time control systems

Mehmet Önder EFE, Coşku KASNAKOĞLU

Risk-averse optimal bidding strategy for a wind energy portfolio manager including EV parking lots for imbalance mitigation

Alper ÇİÇEK, Ozan ERDİNÇ

A multiple sensor fusion based drift compensation algorithm for mecanum wheeled mobile robots

Abdulrahman ALHALABI, Mert EZIM, Kansu Oguz CANBEK, Eray A. BARAN

Low communication parallel distributed adaptive signal processing (LC-PDASP) architecture for processing-inefficient platforms

Hasan RAZA, Ghalib HUSSAIN, Noor M. KHAN

Haze-level prior approach to enhance object visibility under atmospheric degradation

Vijaya Lakshmi THIRUMALA, Venkata SatyaNarayana KARANAM, Pratap Reddy LANKIREDDY, Aruna Kumari KAKUMANI, Rakesh Kumar YACHARAM