Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal International Journal of Power Electronics and Drive Systems (IJPEDS)
Mencou, Siham
Unknown Affiliation
Control & Systems Engineering Electrical & Electronics Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Direct torque control of induction motor based on double-power-super-twisting sliding mode speed control for electric vehicle applications Mencou, Siham; Yakhelf, Majid Ben; Tazi, Elbachir
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i3.pp1399-1409

Abstract

To improve the performance and energy efficiency of the direct torque control of induction motors used in electric vehicles a double-power-super-twisting sliding mode control (DPSTA SMC) strategy has been introduced in the closed speed loop. This strategy is based on the novel double-power-super-twisting algorithm (DPSTA), which combines the performance of the traditional super-twisting algorithm (STA) with the double power reaching law (DPRL). The stability of the algorithm has been proven using a quasi-quadratic Lyapunov function. The performances of the proposed DPSTA SMC controller have been compared with that of PI, fuzzy logic, and STA SMC controllers. Detailed simulations are carried out using MATLAB/Simulink software. The results demonstrate that this approach effectively improves tracking accuracy, system robustness and energy efficiency, while significantly reducing the chattering phenomenon.
Single-neuron adaptive double-power super-twisting sliding mode control for induction motor Mencou, Siham; Yakhlef, Majid Ben; Tazi, El Bachir
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 2: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i2.pp840-850

Abstract

Direct torque control is a widely used control method for induction motors because it offers rapid dynamic response and relatively simple implementation. However, it presents high torque and flux ripples and variable switching frequencies. To overcome these constraints, the double-power super-twisting sliding mode (DPSTSM) control approach has been proposed, integrating the advantages of the super-twisting algorithm designed to reduce chattering with those of the double power convergence law aimed to improve system speed and dynamic quality. However, the optimal tuning of the sliding mode gains of the double-power super-twisting sliding mode controller represents a considerable challenge. To address this issue, we proposed an improvement to the DPSTSM algorithm through the integration of a single-neuron adaptive algorithm. The single-neuron adaptive double-power super-twisting sliding mode control approach aims to dynamically adjust the controller gains, while delivering superior performance in terms of chattering reduction, improved dynamic response, and enhanced robustness to load disturbances. A detailed investigation was carried out via MATLAB/Simulink simulations to determine the effectiveness of the proposed control strategy.
Co-Authors Tazi, El Bachir Tazi, Elbachir Yakhelf, Majid Ben Yakhlef, Majid Ben