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All Journal IAES International Journal of Robotics and Automation (IJRA)
Mahabadi, Arezoo
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Automotive Engineering Electrical & Electronics Engineering

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Enhancing efficiency and reliability in high-power microwave amplifiers: a novel circuit driver approach Jebelli, Ali; Lotfi, Nafiseh; Partovibakhsh, Maral; Mahabadi, Arezoo; Zare, Mohammad Saeid
IAES International Journal of Robotics and Automation (IJRA) Vol 14, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v14i1.pp82-92

Abstract

This paper introduces an innovative circuit driver engineered to significantly enhance the efficiency and longevity of high-power microwave amplifiers, addressing critical limitations of traditional drivers in handling high-power systems. The proposed design features advanced voltage sequencing, which is crucial for extending component life and ensuring safe operation within the safe operating area (SOA). By integrating a sophisticated circuit board with real-time feedback sensors, controlled by a microcontroller, the system ensures continuous monitoring and rapid response to potential operational hazards. The driver automatically engages a fail-safe mode when thresholds are breached, prioritizing efficiency optimization and minimizing energy waste. Rigorous testing has confirmed the circuit driver’s capability to meet and exceed the stringent demands of high-power microwave amplifier applications. This work offers a robust, reliable solution that not only overcomes existing challenges but also sets a new standard for the performance and safety of microwave amplification systems, making it a valuable contribution to the field of power electronics.
Designing and implementing a multi-function board to increase the operation time of mobile robots using solar panels Jebelli, Ali; Mahabadi, Arezoo
IAES International Journal of Robotics and Automation (IJRA) Vol 12, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v12i3.pp248-261

Abstract

Today, the use of mobile robots and autonomous vehicles has increased due to their use in various industries, and their performance and duration of operation largely depend on the amount of energy consumed and their batteries. One of the ways to increase the operation time of robots is the use of solar panels that can charge their batteries while moving, but the amount of energy received from solar panels reduces their efficiency due to factors affecting them, such as the angle of the sun, weather conditions, and their use in mobile robots alone is not recommended. In this research, we introduce an electric circuit with very low losses to increase the received power of solar panels and increase their efficiency, which is able to supply the power of the robot through solar panels when the sunlight and the angle of radiation are suitable and charge the batteries through the maximum power point controller (MPPC), and by reducing the amount of energy received from the panels by changing the energy source to the battery, the duration of the system’s dependence on the battery has decreased, which increases the duration of the mobile robots.
Increasing the operating depth of an autonomous underwater vehicle using an intelligent magnetic field Jebelli, Ali; Mahabadi, Arezoo; Chaoui, Hicham; Yagoub, Mustapha C. E.
IAES International Journal of Robotics and Automation (IJRA) Vol 10, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v10i3.pp207-223

Abstract

Designing and manufacturing a suitable body is one of the most effective factors in increasing the efficiency of autonomous underwater vehicles (AUVs). In fact, increasing the propulsive power of an AUV by reducing the frictional drag on its body and increasing its maneuverability will positively affect key parts of the AUV’s hardware and software such as control system, sensors, AUV vision, batteries and thrusters. On the other hand, a suitable body should have features such as lightness, underwater vehicle’s balance, high mechanical strength, and enough space for equipment. Therefore, the design and manufacture of the body requires a lot of analysis in terms of body material, aerodynamic calculations, etc., increases the overall cost. This paper aims to reduce the stress in the body of a Polytetrafluoroethylene (PTFE) underwater robot and to increase its operating depth without changing the body’s structure by using fuzzy logic to intelligently controlling the magnetic force generated by the repulsion between the coil and the cylindrical magnet, which saves energy, reduces battery consumption, and increases system performance. The results show that the robot performance depth increases by more than 50% without changing the robot body structure.
Fault tolerance of a quadrotor via feedback linearization approach Jebelli, Ali; Najafiyanfar, Alireza; Mahabadi, Arezoo; E. Yagoub, Mustapha C.
IAES International Journal of Robotics and Automation (IJRA) Vol 12, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v12i3.pp228-239

Abstract

A control algorithm is proposed to efficiently control the state, position, and height of a nonlinear dynamic model of a quadcopter. Based on feedback linearization, a state space model is presented for the system with the controller with a two-loop control structure designed and implemented in it. The inner and faster controller is responsible for adjusting the quadcopter height and angles, and the outer and slower controller is responsible for changing the desired figures of roll and pitch angles to control the system position. Whenever a rotor of the quadcopter rotor fails, the status and position of the system are converged and the system is stabilized. Simulation results based on different scenarios indicate the proper performance of the control system whenever there are external disturbances. Note that the gyroscopic effects because of the propeller rotation were not considered.
Efficient commercial classification of agricultural products using convolutional neural networks Jebelli, Ali; Mahabadi, Arezoo; Ahmad, Rafiq
IAES International Journal of Robotics and Automation (IJRA) Vol 10, No 4: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v10i4.pp353-364

Abstract

Agricultural products, as essential commodities, are among the most sought - for items in superstores. Barcode is usually utilized to classify and regulate the price of products such as ornamental flowers in such stores. However, the use of barcodes on some fragile agricultural products such as ornamental flowers can be damaged and lessen their life length. Moreover, it is time - consuming and costly and may lead to the pro duction of massive waste and damage to the environment and the admittance of chemical materials into food products that can affect human health. Consequently, we aimed to design a classifier robot to recognize ornamental flowers based on the related produc t image at different times and surrounding conditions. Besides, it can increase the speed and accuracy of distinguishing and classifying the products, lower the pricing time, and increase the lifetime due to the absence of the need for movement and changin g the position of the products. According to the datasheets provided by the robot that is stored in its database, we provide the possibility of identifying and introducing the product in different colors and shapes. Also, due to the preparation of a standa rd and small database tailored to the needs of the robot, the robot will be trained in a short time (less than five minutes) without the need for an Internet connection or a large hard drive for storage the data. On the other hand, by dividing each input p hoto into ten different sections, the system can, without the need for a detection system, simultaneously in several different images, decorative flowers in different conditions, angles and environments, even with other objects such as vases, detects very fast with a high accuracy of 97%.
Co-Authors Ahmad, Rafiq Chaoui, Hicham E. Yagoub, Mustapha C. Jebelli, Ali Lotfi, Nafiseh Najafiyanfar, Alireza Partovibakhsh, Maral Yagoub, Mustapha C. E. Zare, Mohammad Saeid