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All Journal International Journal of Robotics and Control Systems
Najem, Adil
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Control & Systems Engineering Electrical & Electronics Engineering

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Simulation and Arduino Hardware Implementation of ACO, PSO, and FPA Optimization Algorithms for Speed Control of a DC Motor Najem, Adil; Moutabir, Ahmed; Ouchatti, Abderrahmane
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1483

Abstract

This article proposes implementing and comparing the effectiveness of three optimization algorithms (ACO, PSO, and FPA) for tuning a proportional-integral-derivative (PID) controller on an Arduino Mega 2560 board. This relatively unexplored approach aims to evaluate these algorithms through practical experiments. The choice of PID control is due to its design simplicity and widespread industrial use. Similarly, the permanent magnet DC motor (PMDC) was selected because of its crucial role in various industrial sectors. Tuning PID parameters using optimization algorithms has garnered increasing interest due to its demonstrated efficiency. Several studies have validated the stability of ACO, PSO, and FPA algorithms, justifying their selection. In this article, simulation results showed that ACO, with a response time of 0.322s and an overshoot of 0.68%, was more effective than PSO, which had a response time of 0.768s and an overshoot of 13%. FPA had a response time of 0.347s, close to ACO, but a higher overshoot of 6%. In practice, several factors come into play, such as speed ripples caused by the speed sensor, and machine saturation, which must be considered to ensure practical implementation. After adjusting the PID parameters and integrating a low-pass filter in the feedback loop, ACO, with a response time of 0.596s and an overshoot of 1.68%, was very close to FPA, which had a response time of 0.644s and an overshoot of 0.81%. This comparison highlighted the advantages of the FPA algorithm, which is simple to use, requires fewer parameters to adjust, and takes less time than ACO. This study suggests the potential for implementing a hybrid FPA-ACO algorithm, leveraging the strengths of both algorithms.
Experimental Validation of the Generation of Direct and Quadratic Reference Currents by Combining the Ant Colony Optimization Algorithm and Sliding Mode Control in PMSM using the Process PIL Najem, Adil; Moutabir, Ahmed; Ouchatti, Abderrahmane; Haissouf, Mohammed El
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.v4i1.1286

Abstract

This article aims to enhance the control efficiency of the Permanent Magnet Synchronous Motor (PMSM) by generating optimal reference currents  and using Ant Colony Optimization (ACO), while ensuring a minimal absorbed current condition to reduce energy consumption and optimize PMSM performance. The ACO algorithm is chosen for its ability to find global solutions and robustness in complex environments, while Sliding Mode Control (SMC) provides advantages in terms of robustness against disturbances and the ability to maintain the system in a desired state. The implementation of the processor-in-the-loop (PIL) technique using MATLAB software with code composer and the LAUNCHXL- F28069M board enables the controller to be implemented in real hardware (LAUNCHXL-F28069M) to test the simulation environment (inverter and PMSM). Our results demonstrate the efficiency of ACO compared to the analytical method (AM) in terms of response time and minimizing absorbed current for different load values. Artificial intelligence (AI) has successfully and efficiently addressed the non-linearity between torque and reference currents, thus reducing energy consumption. This has allowed for the optimization of PMSM performance in a straightforward and efficient manner.
Co-Authors Haissouf, Mohammed El Moutabir, Ahmed Ouchatti, Abderrahmane