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An Enhanced DC-Link Voltage Response for Wind-Driven Doubly Fed Induction Generator Using Adaptive Fuzzy Extended State Observer and Sliding Mode Control

Author

Listed:
  • Mohammed Mazen Alhato

    (Research Laboratory in Automatic Control (LARA), National Engineering School of Tunis, BP 37, Le Belvédère, Tunis 1002, Tunisia)

  • Mohamed N. Ibrahim

    (Department of Electromechanical, Systems and Metal Engineering, Ghent University, 9000 Ghent, Belgium
    FlandersMake@UGent—Corelab EEDT-MP, 3001 Leuven, Belgium
    Electrical Engineering Department, Kafrelsheikh University, Kafrelsheikh 33511, Egypt)

  • Hegazy Rezk

    (College of Engineering at Wadi Addawaser, Prince Sattam Bin Abdulaziz University, Al-Kharj 11911, Saudi Arabia
    Electrical Engineering Department, Faculty of Engineering, Minia University, Minia 61517, Egypt)

  • Soufiene Bouallègue

    (Research Laboratory in Automatic Control (LARA), National Engineering School of Tunis, BP 37, Le Belvédère, Tunis 1002, Tunisia
    High Institute of Industrial Systems of Gabès (ISSIG), University of Gabès, Omar Ibn Khattab, Gabès 6029, Tunisia)

Abstract

This paper presents an enhancement method to improve the performance of the DC-link voltage loop regulation in a Doubly-Fed Induction Generator (DFIG)- based wind energy converter. An intelligent, combined control approach based on a metaheuristics-tuned Second-Order Sliding Mode (SOSM) controller and an adaptive fuzzy-scheduled Extended State Observer (ESO) is proposed and successfully applied. The proposed fuzzy gains-scheduling mechanism is performed to adaptively tune and update the bandwidth of the ESO while disturbances occur. Besides common time-domain performance indexes, bounded limitations on the effective parameters of the designed Super Twisting (STA)-based SOSM controllers are set thanks to the Lyapunov theory and used as nonlinear constraints for the formulated hard optimization control problem. A set of advanced metaheuristics, such as Thermal Exchange Optimization (TEO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Harmony Search Algorithm (HSA), Water Cycle Algorithm (WCA), and Grasshopper Optimization Algorithm (GOA), is considered to solve the constrained optimization problem. Demonstrative simulation results are carried out to show the superiority and effectiveness of the proposed control scheme in terms of grid disturbances rejection, closed-loop tracking performance, and robustness against the chattering phenomenon. Several comparisons to our related works, i.e., approaches based on TEO-tuned PI controller, TEO-tuned STA-SOSM controller, and STA-SOSM controller-based linear observer, are presented and discussed.

Suggested Citation

  • Mohammed Mazen Alhato & Mohamed N. Ibrahim & Hegazy Rezk & Soufiene Bouallègue, 2021. "An Enhanced DC-Link Voltage Response for Wind-Driven Doubly Fed Induction Generator Using Adaptive Fuzzy Extended State Observer and Sliding Mode Control," Mathematics, MDPI, vol. 9(9), pages 1-18, April.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:9:p:963-:d:543305
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    References listed on IDEAS

    as
    1. Junzhang Qian & Ai Xiong & Wenli Ma, 2016. "Extended State Observer-Based Sliding Mode Control with New Reaching Law for PMSM Speed Control," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-10, June.
    2. Linyun Xiong & Penghan Li & Hao Li & Jie Wang, 2017. "Sliding Mode Control of DFIG Wind Turbines with a Fast Exponential Reaching Law," Energies, MDPI, vol. 10(11), pages 1-19, November.
    3. Oscar Barambones & Jose A. Cortajarena & Patxi Alkorta & Jose M. Gonzalez De Durana, 2014. "A Real-Time Sliding Mode Control for a Wind Energy System Based on a Doubly Fed Induction Generator," Energies, MDPI, vol. 7(10), pages 1-22, October.
    4. Mohamed, Mohamed A. & Zaki Diab, Ahmed A. & Rezk, Hegazy, 2019. "Partial shading mitigation of PV systems via different meta-heuristic techniques," Renewable Energy, Elsevier, vol. 130(C), pages 1159-1175.
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