___

• [1] Solberg O. A New Wind Turbine Control Method to Smooth Power Generation - Modelling and Comparison to Wind Turbine Frequency Control (MSc). Chalmers University of Technology, Sweden, 2012.
• [2] Billings SA, Chen S, Korenberg MJ. Identification of MIMO non-linear systems using a forward-regression orthogonal estimator. International journal of control 1989; 49(6): 2157-2189.
• [3] Subudhi B, Ogeti PS. Non-linear autoregressive moving average with exogenous input model-based adaptive control of a wind energy conversion system. The Journal of Engineering 2016; 2016(7): 218-226.
• [4] Johansen TA, Foss B. Constructing NARMAX models using ARMAX models. International journal of control 1993; 58(5): 1125-1153.
• [5] Bekker JC. Efficient modelling of a wind turbine system for parameter estimation applications (PhD), Stellenbosch University, Stellenbosch, South Africa, 2012.
• [6] Cadenas E, Rivera W. Wind speed forecasting in three different regions of Mexico using a hybrid ARIMA–ANN model. Renewable Energy 2010; 35(12): 2732-2738.
• [7] Perez-Llera C, Fernandez-Baizan MC, Feito JL, González del Valle V. Local short-term prediction of wind speed: a neural network analysis. In: 1st International Congress on Environmental Modelling and Software; 24-27 June 2002, Switzerland: Brigham Young University Scholars Archives, pp.124-129.
• [8] Nur Dalila Binti Khirul Ashar, Zakiah Mohd Yusoff, Nurlaila Ismail, Muhammad Asraf Hairuddin. ARX Model Identification for the Real-Time Temperature Process with MATLAB-ARDUINO Implementation. ICIC Express Letter 2020; 14(2): 103-111.
• [9] MATLAB R2020b Documentation – System Identification Toolbox, Accessed from https://www.mathworks.com/help/ident/?s_tid=srchbrcm, Accessed on October 2020.
• [10] Muhammad Junaid Rabbani, Kashan Hussain, Asim-ur-Rehman khan, Abdullah Ali. Model Identification and Validation for a Heating System using MATLAB System Identification Toolbox, 2013 IOP Conf. Ser.: Mater. Sci. Eng.51 012022.
• [11] Vijayalaxmi1, Shanmuga Vadivoo. Identification of Doubly Fed Induction Generator based Wind Energy Conversion System Using Piecewise-Linear Hammerstein Wiener Model, Proceedings of 7th International Conference on Intelligent Systems and Control 2013: 37 – 43.
• [12] Lin WM, Hong CM, Cheng FS. On-line designed hybrid controller with adaptive observer for variable-speed wind generation system. Energy 2010, 35(7): 3022-3030.
• [13] Barambones O, de Durana JG, De la Sen M. Robust speed control for a variable speed wind turbine. International Journal of Innovative Computing, Information and Control 2012, 8(11):7627-7640.
• [14] Munteanu I, Bratcu AI, Cutululis NA, Ceanga E. Optimal control of wind energy systems: towards a global approach. London, England: Springer-Verlag London, 2008.
• [15] Aroussi HA, Ziani E, Bossoufi B. Speed control of the doubly fed induction generator applied to a wind system. Journal of Theoretical and Applied Information Technology 2016; 83(3): 426-433.
• [16] Osmic J, Kusljugic M, Becirovic E, Toal D. Analysis of active power control algorithms of variable speed wind generators for power system frequency stabilization. Turkish Journal of Electrical Engineering & Computer Sciences 2016; 24(1): 234-246.
• [17] Jalali M. DFIG based wind turbine contribution to system frequency control (MSc). University of Waterloo, Ontario, Canada, 2011.
• [18] Adel Ab-BelKhair, Javad Rahebi, Abdulbaset Abdulhamed Mohamed Nureddin. A Study of Deep Neural Network Controller-Based Power Quality Improvement of Hybrid PV/Wind Systems by Using Smart Inverter. International Journal of Photoenergy2020, 2020.
• [19] Abdulbaset Abdulhamed Mohamed Nureddin, Javad Rahebi, Adel Ab-BelKhair. Power Management Controller for Microgrid Integration of Hybrid PV/Fuel Cell System Based on Artificial Deep Neural Network. International Journal of Photoenergy 2020, 2020.
• [20] Yasmine Ihedrane, Chakib El Bekkali, Badre Bossoufi, Manale Bouderbala. Control of Power of a DFIG Generator with MPPT Technique for Wind Turbines Variable Speed. In: Modelling, Identification and Control Methods in Renewable Energy Systems, Green Energy and Technology 2019; Springer Nature Singapore Pte Ltd., N. Derbel, Q. Zhu (eds.), pp. 105-127.
• [21] Hassane Mahmoudi, Marouane El Azzaoui, Chafik Ed-Dahmani. Zed Board-FPGA Control of the DFIG Based Wind Power System. In: Modeling, Identification and Control Methods in Renewable Energy Systems, Green Energy and Technology 2019; Springer Nature Singapore Pte Ltd., N. Derbel, Q. Zhu (eds.), pp. 333 -355.
• [22] Abdelbaset A, Mohamed YS, El-Sayed AH, Ahmed AE. Wind Driven Doubly Fed Induction Generator: Grid Synchronization and Control. Geneva, Switzerland: Springer International Publishing, 2018.
• [23] Vestas. General Specification V90–1.8/2.0 MW 50 Hz VCS: Document no.: 0004-6207 V05. Copenhagen, Denmark: Vestas Wind Systems A/S, 2010.
• [24] Simões, M. Godoy, Farret, A. Felix. Renewable Energy Systems: Design and Analysis with Induction Generators. California, USA: CRC Press, 2004.
• [25] Atacak I, Küçük B. PSO-Based PID Controller Design for an Energy Conversion System Using Compressed Air. Tehnicki Vjesnik/Technical Gazette 2017, 24(3): 671-679.
• [26] Woo ZW, Chung HY, Lin JJ. A PID type fuzzy controller with self-tuning scaling factors. Fuzzy sets and systems 2000, 115(2): 321-326.
• [27] Güzelkaya M, Eksin I, Yeşil E. Self-tuning of PID-type fuzzy logic controller coefficients via relative rate observer. Engineering applications of artificial intelligence 2003, 16(3): 227-236.
• [28] Qiao WZ, Mizumoto M. PID type fuzzy controller and parameters adaptive method. Fuzzy sets and systems 1996, 78(1), 23-35.
• [29] Jantzen J. Tuning of fuzzy PID controllers. In Rames C. P., Introduction to PID Controllers - Theory, Tuning and Application to Frontier Areas, Technical University of Denmark, Denmark: IntechOpen, 1998, 171-190.
• [30] Ogata K. Modern Control Engineering: Mathematical Modelling of Control Systems. New Jersey, USA: Prentice Hall, 2010.
• [31] Nadhir A, Naba A, Hiyama T. FIS/ANFIS based optimal control for maximum power extraction in variable-speed wind energy conversion system. IEEJ Transactions on Power and Energy 2011; 131(8): 708-714. DOI: 10.1541/ieejpes.131.708
• [32] Aydin E, Polat A, Ergene LT. Vector control of DFIG in wind power applications. In: IEEE International Conference on Renewable Energy Research and Applications (ICRERA); Nov 20 2016: IEEE, pp. 478-483.