Sezgisel Optimizasyon Kullanarak DC Motor Hız Kontrol Performansının Artırılması ve Kontrol Yöntemlerinin Karşılaştırmalı Analizi

Year 2024, Volume: 12 Issue: 4, 2220 - 2244, 23.10.2024

Beytullah Bozali , Nasser Bandar Nasser Al Saremi , Ali Öztürk

https://doi.org/10.29130/dubited.1505316

Abstract

Doğru Akım (DA) motorları, endüstriyel uygulamalardan ev aletlerine kadar geniş bir yelpazede kullanılan, elektrik enerjisini mekanik enerjiye dönüştüren önemli bir bileşendir. DA motor hız kontrolü, endüstriyel süreçlerde verimliliği artırmak, hassas hareketleri gerçekleştirmek ve enerji tüketimini optimize etmek için önemli bir role sahiptir. Bu çalışmada, yaygın kullanım alanlarına sahip DA motorlarının hız kontrolü için çeşitli kontrol yöntemleri ve parametre optimizasyon teknikleri sistematik bir şekilde analiz edilmiştir. Çalışmanın amacı DA motorların farklı hızlarda gerçek zamanlı olarak izleyerek belirlenen hedef hıza ulaşmasını sağlamak ve değişken yükler veya dış etkenlerden kaynaklanan dalgalanmaları minimize etmek için etkili bir kontrol stratejisi geliştirmektir. Çalışmamızda Oransal-İntegral-Türev (PID), Oransal-İntegral (PI), ve Oransal- Türev (PD) kontrol yöntemleri kullanılmıştır. Bu kontrolörlerin parametreleri, Matlab Tuned, yeni nesil sezgisel optimizasyon yöntemi olan Çita Optimizasyon (CO) Algoritması ve geniş kabul görmüş optimizasyon yöntemi olan Parçacık Sürü Optimizasyonu (PSO) kullanılarak ayarlanmıştır. Kontrolörlerin performanslarını, Hatanın Mutlak Değerinin İntegrali (IAE), Hata Karenin İntegrali (ISE) ve Zaman Mutlak Hatanın İntegrali (ITAE) gibi kriterler kullanılarak belirlenmiştir. Elde edilen sonuçlar göre, CO Algoritması kullanılarak belirlenen PID, PI ve PD kontrol parametrelerinin, Matlab Tuned ve PSO yöntemleri kullanılarak oluşturulan kontrolörlerden daha iyi performans gösterdiği bulunmuştur. CO Algoritması gibi yeni optimizasyon yöntemlerinin, kontrol sistemlerinin performansını artırmak için önemli bir potansiyel taşıdığını bulunmuştur. Bu çalışma sayesinde, endüstriyel süreçlerde DA motor hız kontrolünün optimize edilmesi için pratik bir yaklaşım sunmaktadır. Sonuç olarak, CO Algoritmasıyla belirlenen kontrol parametrelerinin, diğer optimizasyon yöntemlerine göre DA motor hız kontrolünde ve kontrol sistemlerinin performansını iyileştirmede önemli potansiyele sahip olduğu bulunmuştur.

Keywords

CO Algoritması, PSO, PID, PI, PD, DA Motor Kontrol

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

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.

Keywords

CO Algorithm, PSO, PID, PI, PD, DC Motor Control

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