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All Journal International Journal of Robotics and Control Systems Journal of Fuzzy Systems and Control (JFSC)
Aziz, Ghada Adel
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Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Performance Enhancement of DC Motor Drive Systems Using Genetic Algorithm-Optimized PID Controller for Improved Transient Response and Stability Aziz, Ghada Adel; Abdullah, Fatin Nabeel; Shneen, Salam Waley
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.v5i1.1602

Abstract

Some systems require mechanical power, which can be used in many applications, including rotating vehicle wheels, pulling elevators, and moving robot limbs, etc. Mechanical or kinetic energy can be produced and generated from electrical machines, which can be represented by an electric motor, which is a machine that operates on electrical energy, i.e. input energy, and produces mechanical energy, i.e. output energy. One of the most common and widely used motors is the DC motor, which has features that make it a matter of interest to researchers, producing and manufacturing companies to develop and improve its performance. The motor is characterized by flexibility, low cost, durability, and the ability to control the speed and position of the rotating member using traditional, expert and intelligent control systems to achieve appropriate performance according to the field of application. In linear systems, traditional systems (Proportional-Integral-Derivative Controller (PID) have succeeded, while their performance is weak and unacceptable in nonlinear systems. Therefore, expert and intelligent control systems are relied upon to improve the performance of electric motors. It is proposed to implement and operate an electric motor control system using the genetic algorithm to verify its effectiveness in improving performance compared to the traditional one (PID). The genetic algorithm was chosen to address the optimization challenges because it is commonly used in artificial intelligence applications in various fields that are suitable for real time. Therefore, this study presented improving the performance of the traditional controller using the genetic algorithm. Through comparison, the possibility of improving the system performance with changing operating conditions was verified by adjusting the parameters of the traditional controller. The simulation was performed using Matlab, and the DC motor specifications included a rated voltage of 32.4 V, a rated current of 2 A, a rated speed of 536 rad/s, and a power of 54 watts. The conventional controller is responsible for the basic feedback control, while the GA-PID controller optimizes the control parameters to improve the system performance.
Improving TCP/AQM Network Stability Using BBO-Tuned FLC Nadhim, Rasha F.; Oudah, Manal Kadhim; Aziz, Ghada Adel; Shneen, Salam Waley
International Journal of Robotics and Control Systems Vol 5, No 2 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i2.1761

Abstract

One of the modern technologies used to improve the performance of various systems, including communications networks and the Internet, is the technology based on biogeography (BBO) that many researchers in the field of automation and control have shed light on. Fuzzy logic is one of the expert systems that has dealt with its use in control systems by many researchers within different applications. The current work has shed light on the mechanism of using The Biogeography Based-Optimization (BBO) technique for adjusting FLC parameters is called (BBO-FLC). The simulation was performed using Matlab program and the researchers adopted the technique as part of the stability of TCP network. The performance of the techniques used in the optimization process can be identified by comparing the results of each case, such as the proposed technique, with other types represented by the traditional control type Proportional–integral–derivative controller (PID). The possibility of using modern and intelligent optimization techniques for the optimal controller is tested using a tuning process for the parameters of the fuzzy type expert controller with the help of the biogeography-based optimization (BBO) technique. The contributions of the research are to verify the possibility of improving the performance by comparing the behavior of the system for the proposed test and simulation cases by obtaining the prescribed level and without exceeding the permissible values.
GWO-PID of Two-phase Hybrid Stepping Motor for Robotic Grinding Force Abdullah, Fatin Nabeel; Aziz, Ghada Adel; Shneen, Salam Waley
Journal of Fuzzy Systems and Control Vol. 1 No. 3 (2023): Vol. 1, No. 3, 2023
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v1i3.91

Abstract

The use of the computer program MATLAB is prominent in many studies that simulate many industrial systems. The current simulation aims to build a suitable simulation model representing the Two-phase Hybrid Stepping Motor (2Ph-HSM). This type of motor is employed in a specific application to produce a force called automatic grinding force. To control the force, motor speed, and location, we need to add control systems, so two methods have been proposed, one of which is traditional, namely proportional, integral, and derivative (PID) control and the other is intelligent, called Gray Wolf Optimization (GWO). The current work also aims to use traditional control algorithms and advanced optimization algorithms that were chosen for their ease of control and possibility of use in many industrial applications. By setting appropriate specifications for the simulation model and after conducting prescribed tests that simulate different applications of the motor’s work within electrical systems, the results demonstrated good motor performance, better response, and high accuracy, in addition to speed. The goal is to design and tune a proportional, integral, and derivative (PID) controller by gray wolf optimization (GWO) using the transfer function (TF) of a 2Ph-HSM. To adjust the parameters of conventional controllers using advanced optimization, a suitable mechanism and technique were selected from advanced optimization techniques, where the gray wolf technique algorithm was chosen as an optimization technique and Integrated Time Absolute Error (ITAE) to adjust the parameters of conventional PID controller.
Co-Authors Abdullah, Fatin Nabeel Nadhim, Rasha F. Oudah, Manal Kadhim Salam Waley Shneen