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ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation

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submitted on 2023-10-17, 07:07 and posted on 2023-10-17, 11:42 authored by Said Mahfoud, Aziz Derouich, Atif Iqbal, Najib El Ouanjli

Direct Torque Control (DTC) presents an optimal solution to control the behaviors of the alternative motors, compared to other controls, because of several advantages offered by this technique, the speed overshoots, fluxes, and torque ripples remain the major factors which minimize the DTC robustness. The regulation speed in DTC is carried out by the classic Proportional Integrator Derivative (PID), which is known for its higher robustness in linear systems, except that in the case of non-linear systems, the PID controller gives poor reactions to variations in the system’s parameters. The best solutions adopted in this situation are often based on optimization algorithms that generate the controller’s gains in each period where there is an internal or external perturbation, adapting the behaviors of the PID against the system’s nonlinearity. For that reason, this work is focused on the theoretical studies and experimental validation on dSPACE Board DS1104 of the new proposed approach based on PID speed regulation, optimized by the Ant Colony Optimization algorithm (ACO) for DTC, applied to both sides of the Doubly Fed Induction Motor (DFIM), to overcome the previous drawbacks cited at the beginning. The new combined ACO-DTC strategy has been studied for optimizing the gains of the PID controller by using a cost function such as Integral Square Error (ISE). The proposed approach is implemented on Matlab/Simulink to validate the objectives adopted by this strategy. The simulation and experimental results extracted from Matlab and ControlDesk have proved the efficiency of the proposed ACO-DTC with the system’s nonlinearity, which attribute different enhancements in the global system performance.

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Published in: Energy Reports
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Open Access funding provided by the Qatar National Library



  • English



Publication Year

  • 2022

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This Item is licensed under the Creative Commons Attribution 4.0 International License

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  • Qatar University
  • College of Engineering - QU

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