Enhancing DC Motor Speed Control Performance Using Heuristic Optimization and Comparative Analysis of Control Methods

Direct Current (DC) motors are an important component that converts electrical energy into mechanical energy, used in a wide range of applications from industrial applications to home appliances. DC motor speed control has an important role in industrial processes to increase efficiency, realize precise movements and optimize energy consumption. In this study, various control methods and parameter optimization techniques for speed control of DC motors, which have a wide range of applications, have been systematically analyzed. The aim of the study is to develop an effective control strategy to ensure that DC motors reach the determined target speed by monitoring them in real time at different speeds and to minimize fluctuations caused by variable loads or external factors. In our study, Proportional-Integral-Derivative (PID), Proportional-Integral (PI), and Proportional-Derivative (PD) control methods were used. The parameters of these controllers were tuned using Matlab Tuned, The Cheetah Optimizer (CO) Algorithm, a new generation heuristic optimization method, and Particle Swarm Optimization (PSO), a widely accepted optimization method. The performances of the controllers were determined using criteria such as Integral of Absolute Error (IAE), Integral Squared Error (ISE), and Integral of Time multiplied by Absolute Error (ITAE). According to the results obtained, it was found that the PID, PI and PD control parameters determined using the CO Algorithm performed better than the controllers created using Matlab Tuned and PSO methods. New optimization methods, such as the CO Algorithm, have been found to have significant potential to improve the performance of control systems. Thanks to this study, it offers a practical approach for optimizing DC motor speed control in industrial processes. As a result, it has been found that the control parameters determined by the CO Algorithm have significant potential in improving the performance of DC motor speed control and control systems compared to other optimization methods.

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Journal
Düzce Üniversitesi Bilim ve Teknoloji Dergisi
Published
2024-10-18
DOI
https://doi.org/10.29130/dubited.1505316
Primary Topic
Advanced Control Systems Design
Type
article
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article

Enhancing DC Motor Speed Control Performance Using Heuristic Optimization and Comparative Analysis of Control Methods

Beytullah Bozalı, Ali Öztürk, Nasser Bandar Nasser Al Saremi
Düzce Üniversitesi Bilim ve Teknoloji Dergisi
Advanced Control Systems Design
article

Enhancing DC Motor Speed Control Performance Using Heuristic Optimization and Comparative Analysis of Control Methods

Beytullah Bozalı, Ali Öztürk, Nasser Bandar Nasser Al Saremi
article en

Abstract

Direct Current (DC) motors are an important component that converts electrical energy into mechanical energy, used in a wide range of applications from industrial applications to home appliances. DC motor speed control has an important role in industrial processes to increase efficiency, realize precise movements and optimize energy consumption. In this study, various control methods and parameter optimization techniques for speed control of DC motors, which have a wide range of applications, have been systematically analyzed. The aim of the study is to develop an effective control strategy to ensure that DC motors reach the determined target speed by monitoring them in real time at different speeds and to minimize fluctuations caused by variable loads or external factors. In our study, Proportional-Integral-Derivative (PID), Proportional-Integral (PI), and Proportional-Derivative (PD) control methods were used. The parameters of these controllers were tuned using Matlab Tuned, The Cheetah Optimizer (CO) Algorithm, a new generation heuristic optimization method, and Particle Swarm Optimization (PSO), a widely accepted optimization method. The performances of the controllers were determined using criteria such as Integral of Absolute Error (IAE), Integral Squared Error (ISE), and Integral of Time multiplied by Absolute Error (ITAE). According to the results obtained, it was found that the PID, PI and PD control parameters determined using the CO Algorithm performed better than the controllers created using Matlab Tuned and PSO methods. New optimization methods, such as the CO Algorithm, have been found to have significant potential to improve the performance of control systems. Thanks to this study, it offers a practical approach for optimizing DC motor speed control in industrial processes. As a result, it has been found that the control parameters determined by the CO Algorithm have significant potential in improving the performance of DC motor speed control and control systems compared to other optimization methods.

Düzce Üniversitesi Bilim ve Teknoloji DergisiVol. 12(4)
Düzce Üniversitesi (TR)
Affordable and clean energy
Openalex Percentile: Top 79%
Advanced Control Systems Design
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