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All Journal Journal of Robotics and Control (JRC) International Journal of Robotics and Control Systems
Zahraoui, Yassine
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Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

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Journal : International Journal of Robotics and Control Systems

 1 
Induction Motor Performance Improvement using Super Twisting SMC and Twelve Sector DTC Zahraoui, Yassine; Moutchou, Mohamed; Tayane, Souad; Fahassa, Chaymae; Elbadaoui, Sara
International Journal of Robotics and Control Systems Vol 4, No 1 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i1.1090

Abstract

Induction motor (IM) direct torque control (DTC) is prone to a number of weaknesses, including uncertainty, external disturbances, and non-linear dynamics. Hysteresis controllers are used in the inner loops of this control method, whereas traditional proportional-integral (PI) controllers are used in the outer loop. A high-performance torque and speed system is consequently needed to assure a stable and reliable command that can tolerate such unsettled effects. This paper treats the design of a robust sensorless twelve-sector DTC of a three-phase IM. The speed controller is conceived based on high-order super-twisting sliding mode control with integral action (iSTSMC). The goal is to decrease the flux, torque, the current ripples that constitute the major conventional DTC drawbacks. The phase current ripples have been effectively reduced from 76.92% to 45.30% with a difference of 31.62%. A robust adaptive flux and speed observer-based fuzzy logic mechanism are inserted to get rid of the mechanical sensor. Satisfactory results have been got through simulations in MATLAB/Simulink under load disturbance. In comparison to a conventional six-sector DTC, the suggested technique has a higher performance and lower distortion rate.
Autonomous Driving Model with Collision Prediction for Urban and Extra-Urban Environments Hafid, Yassine El; Ligabi, Tarik; Zahraoui, Yassine
International Journal of Robotics and Control Systems Vol 5, No 1 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i1.1681

Abstract

This study introduces an architecture for an autonomous vehicle control system based on a collision detector and geometric modeling of trajectories. The goal is to develop a robust and reliable control model that can navigate metropolitan environments, often crowded with pedestrians and bicycles, as well as suburban areas, where traffic patterns can fluctuate. We have created a modular control unit that includes a collision predictor, which interacts closely with the decision module. The executed algorithm demonstrates the effectiveness of our system by ensuring the safety and comfort of the passengers. It can identify potential collisions from a distance and initiate braking preventively, following precise guidelines for deceleration and acceleration. To validate our methods, we are looking at simulations of realistic case studies. The research conducted underscores a crucial advancement in the development of safer and more flexible autonomous driving technologies.
Analyzing the Flow of Injection Molding for Water Filter Handle: Filling, Packing, and Warpage Achor, Zineb; Zahraoui, Yassine; Tayane, Souad; Ennaji, Mohamed; Gaber, Jaafar
International Journal of Robotics and Control Systems Vol 4, No 4 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i4.1561

Abstract

Injection molding is a crucial manufacturing technology for producing complex, high-quality parts at scale, making it essential in various industries, including consumer electronics and automotive sectors. However, a lack of understanding about how injection parameters impact common defects like sink marks, short shots, and warpage often limits the widespread adoption of injection molding. This research aims to bridge this gap by providing a comprehensive digital simulation of the injection molding process within a complex mold cavity. Utilizing Moldex3D and the Finite Volume Method (FVM), this study characterizes essential material properties–viscosity, specific heat, density, and thermal conductivity–and examines the effects of gate location and part design on minimizing weld lines and warpage. The FVM involves dividing the computational domain into a finite number of small control volumes. This method is particularly well-suited for handling complex geometries and flow conditions, facilitating detailed and accurate simulations. This study employs Moldex3D, a leading simulation software in the field of injection molding, to demonstrate the use of CAE for design verification and process innovation. Moldex3D’s advanced capabilities make it an ideal tool for simulating injection molding processes, helping improve the quality of parts and contributing to the overall advancement of molding skills in the industry. The simulations revealed optimal gate locations that significantly improved filling patterns, reduced warpage by 50%, and minimized weld lines, thereby enhancing overall part quality. Key contributions of this research include the identification of critical flow characteristics, the reduction of defect-prone regions, and the enhancement of plastic component rigidity. This study provides valuable insights into optimizing injection molding processes, offering a pathway to improved efficiency and part quality in advanced manufacturing.
Co-Authors Achor, Zineb Alfian Ma’arif Elbadaoui, Sara Ennaji, Mohamed Fahassa, Chaymae Gaber, Jaafar Hafid, Yassine El Ligabi, Tarik Moutchou, Mohamed Tayane, Souad