A New Robust Direct Torque Control Based on a Genetic Algorithm for a Doubly-Fed Induction Motor: Experimental Validation

Said Mahfoud, Aziz Derouich, Najib El Ouanjli, Mahmoud A. Mossa, Mahajan Sagar Bhaskar, Ngo Kim Lan and Nguyen Vu Quynh
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Said Mahfoud: Industrial Technologies and Services Laboratory, Higher School of Technology, Sidi Mohamed Ben Abdellah University, Fez 30000, Morocco
Aziz Derouich: Industrial Technologies and Services Laboratory, Higher School of Technology, Sidi Mohamed Ben Abdellah University, Fez 30000, Morocco
Najib El Ouanjli: Industrial Technologies and Services Laboratory, Higher School of Technology, Sidi Mohamed Ben Abdellah University, Fez 30000, Morocco
Mahmoud A. Mossa: Electrical Engineering Department, Faculty of Engineering, Minia University, Minia 61111, Egypt
Mahajan Sagar Bhaskar: Renewable Energy Lab, College of Engineering, Prince Sultan University, Riyadh 11586, Saudi Arabia
Ngo Kim Lan: Electrical Department, Dong Nai Technical College, Bien Hoa 810000, Vietnam
Nguyen Vu Quynh: Electrical and Electronics Department, Lac Hong University, Bien Hoa 810000, Vietnam

Energies, 2022, vol. 15, issue 15, 1-26

Abstract: The parametric variation of nonlinear systems remains a significant drawback of automatic system controllers. The Proportional–Integral(PI) and Proportional–Integral–Derivative (PID) are the most commonly used controllers in industrial control systems. However, with the evolution of these systems, such controllers have become insufficient to compete with the complexity of the systems. This problem can be solved with the help of artificial intelligence, and especially with the use of optimization algorithms, which allow for variable gains in PID controllers that adapt to parametric variation. This article presents an analytical and experimental study of the Direct Torque Control (DTC) of a Doubly-Fed Induction Motor (DFIM). The speed adaptation of the DFIM is achieved using a PID controller, which is characterized by overshoots in the speed and ripples in the electromagnetic torque. The Genetic Algorithm (GA) within the DTC shows very good robustness in speed and torque by reducing torque ripples and suppressing overshoots. The simulation of the GA-DTC hybrid control in MATLAB/Simulink confirms the improvement offered by this strategy. The validation and implementation of this strategy on the dSPACE DS1104 board are in good agreement with the simulation results and theoretical analysis.

Keywords: Genetic Algorithm–Direct Torque Control (GA–DTC); dSPACE DS1104; control desk; Doubly-Fed Induction Motor (DFIM) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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