An advanced direct torque control for doubly fed induction motor using evolutionary computational techniques

Abstract The doubly-fed induction machine is progressively supplanting the cage machine owing to its superior efficiency in variable-speed applications and improved performance in renewable energy systems. Nonetheless, its complicated mathematical model, derived from the interdependent rotor and sta...

Full description

Saved in:
Bibliographic Details
Main Authors: Said Mahfoud, Najib El Ouanjli, Aziz Derouich, Abderrahman El Idrissi, Elmostafa Chetouani, Azeddine Loulijat, Shimaa A. Hussien, Mohamed I. Mosaad
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-08287-6
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849334973583065088
author Said Mahfoud
Najib El Ouanjli
Aziz Derouich
Abderrahman El Idrissi
Elmostafa Chetouani
Azeddine Loulijat
Shimaa A. Hussien
Mohamed I. Mosaad
author_facet Said Mahfoud
Najib El Ouanjli
Aziz Derouich
Abderrahman El Idrissi
Elmostafa Chetouani
Azeddine Loulijat
Shimaa A. Hussien
Mohamed I. Mosaad
author_sort Said Mahfoud
collection DOAJ
description Abstract The doubly-fed induction machine is progressively supplanting the cage machine owing to its superior efficiency in variable-speed applications and improved performance in renewable energy systems. Nonetheless, its complicated mathematical model, derived from the interdependent rotor and stator dynamics, necessitates more effective control solutions, such as direct torque control (DTC) in doubly-fed induction motor (DFIM) applications. DTC, particularly when integrated with a simple PID controller offers powerful and dynamic performance; yet, it may result in torque ripples owing to hysteresis control and speed overshoot from abrupt torque demand fluctuations. Moreover, careful fine-tuning of the PID controller parameters is necessary. This paper presents a methodology that integrates DTC-based PID controller with two optimization algorithms, with either Genetic algorithm (GA) or ant colony optimization (ACO). These optimization strategies are designed to optimally tune the PID controller settings for speed control improvements and to address internal and external disturbances. Simulation results show that the new hybrid GA-DTC and ACO-DTC controls significantly improve performance. In particular, ACO-DTC reduces torque ripples by 27.86%, improving stability and extending machine life. These methods offer promising prospects for the industrial application of doubly-fed induction motor control systems.
format Article
id doaj-art-d9ef6a31a3ce49be9631e7919ebb1a5f
institution Kabale University
issn 2045-2322
language English
publishDate 2025-07-01
publisher Nature Portfolio
record_format Article
series Scientific Reports
spelling doaj-art-d9ef6a31a3ce49be9631e7919ebb1a5f2025-08-20T03:45:26ZengNature PortfolioScientific Reports2045-23222025-07-0115112710.1038/s41598-025-08287-6An advanced direct torque control for doubly fed induction motor using evolutionary computational techniquesSaid Mahfoud0Najib El Ouanjli1Aziz Derouich2Abderrahman El Idrissi3Elmostafa Chetouani4Azeddine Loulijat5Shimaa A. Hussien6Mohamed I. Mosaad7Polydisciplinary Laboratory of Sciences, Technologies, and Societies, Higher School of Technology, Sultan Moulay Slimane UniversityElectrical Engineering Department, Higher School of Technology, Moulay Ismail UniversityIndustrial Technologies and Services Laboratory, Higher School of Technology, Sidi Mohamed Ben Abdellah UniversityIndustrial Technologies and Services Laboratory, Higher School of Technology, Sidi Mohamed Ben Abdellah UniversityLAVETE Laboratory, Systems Analysis and Information Processing Team, Faculty of Science and Technology, Hassan 1st UniversityLaboratory of Mechanical, Computer, Electronics and Telecommunications, Faculty of Sciences and Technology, Hassan First UniversityElectrical Department, College of Engineering, Princess Nourah Bint Abdulrahman UniversityYanbu Industrial College (YIC) Alnahdah, Yanbu Al SinaiyahAbstract The doubly-fed induction machine is progressively supplanting the cage machine owing to its superior efficiency in variable-speed applications and improved performance in renewable energy systems. Nonetheless, its complicated mathematical model, derived from the interdependent rotor and stator dynamics, necessitates more effective control solutions, such as direct torque control (DTC) in doubly-fed induction motor (DFIM) applications. DTC, particularly when integrated with a simple PID controller offers powerful and dynamic performance; yet, it may result in torque ripples owing to hysteresis control and speed overshoot from abrupt torque demand fluctuations. Moreover, careful fine-tuning of the PID controller parameters is necessary. This paper presents a methodology that integrates DTC-based PID controller with two optimization algorithms, with either Genetic algorithm (GA) or ant colony optimization (ACO). These optimization strategies are designed to optimally tune the PID controller settings for speed control improvements and to address internal and external disturbances. Simulation results show that the new hybrid GA-DTC and ACO-DTC controls significantly improve performance. In particular, ACO-DTC reduces torque ripples by 27.86%, improving stability and extending machine life. These methods offer promising prospects for the industrial application of doubly-fed induction motor control systems.https://doi.org/10.1038/s41598-025-08287-6Doubly fed induction motorDirect torque controlGenetic algorithmAnt Colony Optimization
spellingShingle Said Mahfoud
Najib El Ouanjli
Aziz Derouich
Abderrahman El Idrissi
Elmostafa Chetouani
Azeddine Loulijat
Shimaa A. Hussien
Mohamed I. Mosaad
An advanced direct torque control for doubly fed induction motor using evolutionary computational techniques
Scientific Reports
Doubly fed induction motor
Direct torque control
Genetic algorithm
Ant Colony Optimization
title An advanced direct torque control for doubly fed induction motor using evolutionary computational techniques
title_full An advanced direct torque control for doubly fed induction motor using evolutionary computational techniques
title_fullStr An advanced direct torque control for doubly fed induction motor using evolutionary computational techniques
title_full_unstemmed An advanced direct torque control for doubly fed induction motor using evolutionary computational techniques
title_short An advanced direct torque control for doubly fed induction motor using evolutionary computational techniques
title_sort advanced direct torque control for doubly fed induction motor using evolutionary computational techniques
topic Doubly fed induction motor
Direct torque control
Genetic algorithm
Ant Colony Optimization
url https://doi.org/10.1038/s41598-025-08287-6
work_keys_str_mv AT saidmahfoud anadvanceddirecttorquecontrolfordoublyfedinductionmotorusingevolutionarycomputationaltechniques
AT najibelouanjli anadvanceddirecttorquecontrolfordoublyfedinductionmotorusingevolutionarycomputationaltechniques
AT azizderouich anadvanceddirecttorquecontrolfordoublyfedinductionmotorusingevolutionarycomputationaltechniques
AT abderrahmanelidrissi anadvanceddirecttorquecontrolfordoublyfedinductionmotorusingevolutionarycomputationaltechniques
AT elmostafachetouani anadvanceddirecttorquecontrolfordoublyfedinductionmotorusingevolutionarycomputationaltechniques
AT azeddineloulijat anadvanceddirecttorquecontrolfordoublyfedinductionmotorusingevolutionarycomputationaltechniques
AT shimaaahussien anadvanceddirecttorquecontrolfordoublyfedinductionmotorusingevolutionarycomputationaltechniques
AT mohamedimosaad anadvanceddirecttorquecontrolfordoublyfedinductionmotorusingevolutionarycomputationaltechniques
AT saidmahfoud advanceddirecttorquecontrolfordoublyfedinductionmotorusingevolutionarycomputationaltechniques
AT najibelouanjli advanceddirecttorquecontrolfordoublyfedinductionmotorusingevolutionarycomputationaltechniques
AT azizderouich advanceddirecttorquecontrolfordoublyfedinductionmotorusingevolutionarycomputationaltechniques
AT abderrahmanelidrissi advanceddirecttorquecontrolfordoublyfedinductionmotorusingevolutionarycomputationaltechniques
AT elmostafachetouani advanceddirecttorquecontrolfordoublyfedinductionmotorusingevolutionarycomputationaltechniques
AT azeddineloulijat advanceddirecttorquecontrolfordoublyfedinductionmotorusingevolutionarycomputationaltechniques
AT shimaaahussien advanceddirecttorquecontrolfordoublyfedinductionmotorusingevolutionarycomputationaltechniques
AT mohamedimosaad advanceddirecttorquecontrolfordoublyfedinductionmotorusingevolutionarycomputationaltechniques