A Comparative Study of Interval Type-2 and Type-1 Fuzzy Sliding Mode in Controlling DFIG-Based Wind Energy Conversion System
DOI:
https://doi.org/10.63746/njtd.v22i3.2818Keywords:
Doubly fed induction generator, Wind power, Sliding mode control, Interval type-2 fuzzy Logic control , Type-1 fuzzy logic controlAbstract
This paper explores the use of Interval Type-2 Fuzzy Sliding Mode Control (IT2-FSMC) for managing a double-fed induction generator (DFIG) in wind energy systems. By combining sliding mode control with fuzzy logic, the method effectively mitigates model uncertainty and reduces chatter, a prevalent issue in variable-structure systems. The paper includes a thorough comparison with type-1 fuzzy sliding mode control (T1-FSMC). The proposed control techniques are tested under various conditions, such as changing wind speed and parameter variations, to evaluate their performance. Simulation results show that IT2-FSMC outperforms T1-FSMC in terms of rise time and reference tracking. IT2-FSMC also significantly reduces the integral of the square error (ISE), integral of the absolute error(IAE), integral time absolute error(ITAE), and integral time square error(ITSE), and achieves the lowest values for both active and reactive power, while reducing the current harmonic distortion (THD) to 80.72%. Simulations were performed using MATLAB/Simulink software.
References
Acikgoz, H., Kececioglu, O., Gani, A., Tekin, M., & Sekkeli, M. (2017). Robust control of shunt active power filter using interval type-2 fuzzy logic controller for power quality improvement. Tehnicki Vjesnik-Technical Gazette, 24.
Adeyanju, A. A. (2023). The Influence Of Rotor Separation On The Performance Of A Dual-Rotor Wind Turbine. Journal of Namibian Studies, History Politics Culture, 35, 4684-4702.
Amira, L., Tahar, B., & Abdelkrim, M. (2020). Sliding mode control of doubly-fed induction generator in wind energy conversion system. In 2020 8th International Conference on Smart Grid (icSmartGrid). (pp. 96-100). IEEE.
Bühler, H. (1986). Sliding mode adjustment. EPFL Press.
Castillo, O., & Melin, P. (2012). A review of the design and optimization of interval type-2 fuzzy controllers. Applied Soft Computing, 12(4), 1267-1278.
Castillo, O., Martinez-Marroquin, R., Melin, P., Valdez, F., & Soria, J. (2012). Comparative study of bio-inspired algorithms applied to the optimization of type-1 and type-2 fuzzy controllers for an autonomous mobile robot. Information sciences, 192, 19-38.
Chakib, M., Nasser, T., & Essadki, A. (2020). Comparative study of active disturbance rejection control with RST control for variable wind speed turbine based on doubly fed induction generator connected to the grid. International Journal of Intelligent Engineering and Systems, 13(1), 248-258.
Hassani, H., & Zarei, J. (2015). Interval Type-2 fuzzy logic controller design for the speed control of DC motors. Systems Science & Control Engineering, 3 (1), 266-273.
Heier, S. (2014). Grid integration of wind energy: onshore and offshore conversion systems. John Wiley & Sons.
Hemeyine, A. V., Abbou, A., Tidjani, N., Mokhlis, M., & Bakouri, A. (2020). Robust Takagi Sugeno fuzzy models control for a variable speed wind turbine based on a DFIG. International Journal of Intelligent Engineering and Systems, 13(3), 90-100.
Kadri, A., Marzougui, H., Aouiti, A., & Bacha, F. (2020). Energy management and control strategy for a DFIG wind turbine/fuel cell hybrid system with super capacitor storage system. Energy, 192, 116518.
Kaloi, G. S., Baloch, M. H., Kumar, M., Soomro, D. M., Chaudhary, S. T., Memon, A. A.& Ishak, D. (2019). An LVRT scheme for grid-connected DFIG based WECS using state feedback linearization control technique. Electronics, 8(7), 777.
Karnik, N. N., & Mendel, J. M. (1998, May). Introduction to type-2 fuzzy logic systems. In 1998 IEEE International Conference on Fuzzy Systems proceedings. IEEE World Congress on computational intelligence (Cat. No. 98CH36228) (Vol. 2, pp. 915-920). IEEE.
Khan, D., Ahmed Ansari, J., Aziz Khan, S., & Abrar, U. (2020). Power optimization control scheme for doubly fed induction generator used in wind turbine generators. Inventions, 5(3), 40.
Kheir Saadaoui, B. B., Assas, O., & Khodja, M. A. (2019). Type-1 and type-2 fuzzy sets to control a nonlinear dynamic system. Revue d'Intelligence Artificielle, 33(1), 1-7.
Lathamaheswari, M., Nagarajan, D., Kavikumar, J., & Broumi, S. (2020). Triangular interval type-2 fuzzy soft set and its application. Complex & Intelligent Systems,6, 531-544.
Li, K., Zhang, X., Han, Y. (2023). Robot path planning based on interval type-2 fuzzy controller optimized by an improved Aquila optimization algorithm. IEEE Access.
Liang, Q., & Mendel, J. M. (2000). Interval type-2 fuzzy logic systems: theory and design. IEEE Transactions on Fuzzy Systems, 8(5), 535-550.
Magaji, N., Mustafa, M.W.B., Lawan, A.U., Tukur, A., Abdullahi, I., Marwan, M., (2022). Application of Type 2 fuzzy for maximum power point tracker for photovoltaic system. Processes 10 (8), 1530.
Mancini, M., Capello, E., & Punta, E. (2020). Sliding mode control with chattering attenuation and hardware constraints in spacecraft applications. IFAC-PapersOnLine, 53(2), 5147-5152.
Mendel, J. M. (2000). Uncertainty, fuzzy logic, and signal processing. Signal Processing, 80(6), 913-933.
Mendel, J. M., & John, R. I. (2001, July). A fundamental decomposition of type-2 fuzzy sets. In Proceedings joint 9th IFSA world congress and 20th NAFIPS international conference (Cat. No. 01TH8569) (Vol. 4, pp. 1896-1901). IEEE.
Milles, A., Merabet, E., Benbouhenni, H., Debdouche, N., & Colak, I. (2024). Robust control technique for wind turbine system with interval type-2 fuzzy strategy on a dual star induction generator. Energy Reports, 11, 2715-2736.
Mousa, H. H., Youssef, A. R., & Mohamed, E. E. (2020). Hybrid and adaptive sectors P&O MPPT algorithm based wind generation system. Renewable Energy, 145, 1412-1429.
Mousavi, Y., Bevan, G., Kucukdemiral, I. B., & Fekih, A. (2022). Sliding mode control of wind energy conversion systems: Trends and applications. Renewable and Sustainable Energy Reviews, 167, 112734.
Okedu, K. E., Al Tobi, M., & Al Araimi, S. (2021). Comparative study of the effects of machine parameters on DFIG and PMSG variable speed wind turbines during grid fault. Frontiers in Energy Research, 9, 681443.
Sahri, Y., Tamalouzt, S., Lalouni Belaid, S., Bacha, S., Ullah, N., Ahamdi, A. A. A., & Alzaed, A. N. (2021). Advanced fuzzy 12 dtc control of doubly fed induction generator for optimal power extraction in wind turbine system under random wind conditions. Sustainability, 13(21), 11593.
Scarabaggio, P., Grammatico, S., Carli, R., & Dotoli, M. (2021). Distributed demand side management with stochastic wind power forecasting. IEEE Transactions on Control Systems Technology, 30(1), 97-112.
Shuaibu, M., Abubakar, A. S., & Shehu, A. F. (2021). Techniques for ensuring fault ride-through capability of grid connected dfig-based wind turbine systems: a review. Nigerian Journal of Technological Development, 18(1), 39-46.
Slotine, J. J. E. (1991). Applied nonlinear control. PRENTICE-HALL google schola, 2, 1123-1131
Tan, W. W., & Chua, T. W. (2007). Uncertain rule-based fuzzy logic systems: introduction and new directions (Mendel, JM; 2001)[book review]. IEEE Computational Intelligence Magazine, 2(1), 72-73.
Xiong, L., Li, J., Li, P., Huang, S., Wang, Z., & Wang, J. (2021). Event triggered prescribed time convergence sliding mode control of DFIG with disturbance rejection capability. International Journal of Electrical Power & Energy Systems, 131, 106970.
Yan, S. R., Dai, Y., Shakibjoo, A. D., Zhu, L., Taghizadeh, S., Ghaderpour, E., & Mohammadzadeh, A. (2024). A fractional-order multiple-model type-2 fuzzy control for interconnected power systems incorporating renewable energies and demand response. Energy Reports, 12, 187-196.
Yin, M., Xu, Y., Shen, C., Liu, J., Dong, Z. Y., & Zou, Y. (2016). Turbine stability-constrained available wind power of variable speed wind turbines for active power control. IEEE Transactions on Power Systems, 32(3), 2487-2488.
Zadeh, L. A. (1988). Fuzzy logic. Computer, 21(4), 83-93.

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