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DA Motoru Kapalı Çevrim Hız Denetim Sistemindeki PI Parametrelerinin Genetik ve Parçacık Sürü Algoritması Kullanarak Optimizasyonu

Yıl 2019, Cilt: 2 Sayı: 1, 51 - 60, 13.07.2019

Öz

Bu çalışmada literatürde DA motoru kapalı çevrim
hız denetim sistemindeki PI parametrelerinin optimal ayarı için genetik ve
parçacık sürü algoritması kullanılarak benzetim çalışması yapılmıştır. Sistemin
dinamik tepkisinde oturma zamanı, yükselme zamanı ve maksimum aşım miktarı gibi
performans kriterleri açısından iyileşmeler sağlanarak motor veriminin
artırılması sağlanmıştır. Ayrıca, genetik ve parçacık sürü algoritmasının
karşılaştırılması yapılarak sistemin performansı değerlendirilmiştir. Böylece
kullanılan algoritmalar farklı denetim uygulamalarında da kullanılabilmesine
imkân sunulmuştur

Kaynakça

  • [1] Bal G, Doğru Akım Makinaları ve Sürücüleri Seçkin Yayıncılık, 2001.
  • [2] Singh V, Garg VK, 2016 Tuning of PID controller for speed control of DC motor using soft computing techniques – A Review. International Journal of Applied Engineering Research, 9(9), 1141–1148, 2016.
  • [3] Erkol, HO. “GA ve PSO ile Kontrol Parametrelerinin Optimizasyonu”. Karaelmas Fen ve Muh. Derg. 7(1), 179-185, 2017.
  • [4] Bandaghiri PS, Moradi N, Tehrani SS. “Optimal tuning of PID controller parameters for speed control of DC motor based on world cup optimization algorithm”, Tech J Engin & App Sci, 6(2), 106–111, 2016.
  • [5] Bulut M. Doğru akım moturunun genetic algoritmalar yardımıyla bilgisayar temelli PI-tip bulanık mantık kontrolü, Yıldız Teknik Üniversitesi-Fen Bilimleri Enstitüsü, Doktora Tezi, 2001.
  • [6] Kanojiya R G Meshram P M 2012 Optimal tuning of PI controller for speed control of DC motor drive using particle swarm optimization IEEE International Conference on Advances in Power Conversion and Energy Technologies Mylavaram, Andhra Pradesh, India.
  • [7] Thangaraj R, Chelliah TR, Pant M, Abraham A, Grosan C. “Optimal gain tuning of PI speed controller in induction motor drives using particle swarm optimization”, Logic Journal of IGPL, 19(2), 343 – 356, 2010.
  • [8] Ibrahim HEA, Hassan FN, Shomer A. “Optimal PID control of a brushless DC motor using PSO and BF techniques” Ain Shams Engineering Journal, 5, 391–398, 2014.
  • [9] Ayala HVH, Santos CL. “Tuning of PID controller based on a multi objective genetic algorithm applied to a robotic manipulator”, Expert Syst. Application, (39)10, 8968 – 8974, 2012.
  • [10] Chen J, Omidvar MN, Azad M, Yao X, “Knowledge-based particle swarm optimization for PID controller tuning”, IEEE Congress on Evolutionary Computation, Spain, 2017.
  • [11] Kanojiya RG, Meshram PM, “Optimal tuning of PI controller for speed control of DC motor drive using particle swarm optimization”, IEEE International Conference on Advances in Power Conversion and Energy Technologies, 1–6, 2012.
  • [12] Thangaraj R, Chelliah TR, Pant M, Abraham A, Grosan C, “Optimal gain tuning of PI speed controller in induction motor drives using particle swarm optimization”, Logic Journal of IGPL 19(2) 343–356, 2010.
  • [13] Aggrawal A, Mishra AK, Zeeshan A. “Speed Control of DC Motor Using Particle Swarm Optimization Technique by PSO Tunned PID and FOPID”, International Journal of Engineering Trends and Technology (IJETT), 16(2), 72-79, 2014.
  • [14] Akhilesh K, Narain MA, “Speed Control of Dc Motor Using Particle Swarm Optimization”, International Journal of Engineering Research and Technology, 1 (02), 2012.
  • [15] Altun M, Çelik Y, Güneş M, ”Investigation of The Success of Particle Swarm Optimization Based PID Classic PID and Fuzzy Type Inspection Methods in Speed Control of DC Motor”, Kahramanmaras Sutcu Imam University Journal of Engineering Sciences KSU. Journal of Engineering Sciences, 20(4), 158-167, 2017.
  • [16] Kaushal A, Thakur N, Nagaria D, “Comparison of Speed Control of DC Motor Using Fuzzy- PID and PSO-PID”, Technique International Journal of Information & Computation Technology, 4(6), 553-558, 2014.
  • [17] Ghareaghaji A, “A Comparison between Fuzzy-PSO Controller and PID-PSO Controller for Controlling a DC Motor”, Bulletin of Electrical Engineering and Informatics, 4(2), 130-135, 2015.
  • [18] El-Gammal A, El-Samahy, Adel A. “A Modified Design of PID Controller for DC Motor Drives Using Particle Swarm Optimization”, International Conference on Power Engineering, Energy and Electrical Drives, 419–424, 2009.
Yıl 2019, Cilt: 2 Sayı: 1, 51 - 60, 13.07.2019

Öz

Kaynakça

  • [1] Bal G, Doğru Akım Makinaları ve Sürücüleri Seçkin Yayıncılık, 2001.
  • [2] Singh V, Garg VK, 2016 Tuning of PID controller for speed control of DC motor using soft computing techniques – A Review. International Journal of Applied Engineering Research, 9(9), 1141–1148, 2016.
  • [3] Erkol, HO. “GA ve PSO ile Kontrol Parametrelerinin Optimizasyonu”. Karaelmas Fen ve Muh. Derg. 7(1), 179-185, 2017.
  • [4] Bandaghiri PS, Moradi N, Tehrani SS. “Optimal tuning of PID controller parameters for speed control of DC motor based on world cup optimization algorithm”, Tech J Engin & App Sci, 6(2), 106–111, 2016.
  • [5] Bulut M. Doğru akım moturunun genetic algoritmalar yardımıyla bilgisayar temelli PI-tip bulanık mantık kontrolü, Yıldız Teknik Üniversitesi-Fen Bilimleri Enstitüsü, Doktora Tezi, 2001.
  • [6] Kanojiya R G Meshram P M 2012 Optimal tuning of PI controller for speed control of DC motor drive using particle swarm optimization IEEE International Conference on Advances in Power Conversion and Energy Technologies Mylavaram, Andhra Pradesh, India.
  • [7] Thangaraj R, Chelliah TR, Pant M, Abraham A, Grosan C. “Optimal gain tuning of PI speed controller in induction motor drives using particle swarm optimization”, Logic Journal of IGPL, 19(2), 343 – 356, 2010.
  • [8] Ibrahim HEA, Hassan FN, Shomer A. “Optimal PID control of a brushless DC motor using PSO and BF techniques” Ain Shams Engineering Journal, 5, 391–398, 2014.
  • [9] Ayala HVH, Santos CL. “Tuning of PID controller based on a multi objective genetic algorithm applied to a robotic manipulator”, Expert Syst. Application, (39)10, 8968 – 8974, 2012.
  • [10] Chen J, Omidvar MN, Azad M, Yao X, “Knowledge-based particle swarm optimization for PID controller tuning”, IEEE Congress on Evolutionary Computation, Spain, 2017.
  • [11] Kanojiya RG, Meshram PM, “Optimal tuning of PI controller for speed control of DC motor drive using particle swarm optimization”, IEEE International Conference on Advances in Power Conversion and Energy Technologies, 1–6, 2012.
  • [12] Thangaraj R, Chelliah TR, Pant M, Abraham A, Grosan C, “Optimal gain tuning of PI speed controller in induction motor drives using particle swarm optimization”, Logic Journal of IGPL 19(2) 343–356, 2010.
  • [13] Aggrawal A, Mishra AK, Zeeshan A. “Speed Control of DC Motor Using Particle Swarm Optimization Technique by PSO Tunned PID and FOPID”, International Journal of Engineering Trends and Technology (IJETT), 16(2), 72-79, 2014.
  • [14] Akhilesh K, Narain MA, “Speed Control of Dc Motor Using Particle Swarm Optimization”, International Journal of Engineering Research and Technology, 1 (02), 2012.
  • [15] Altun M, Çelik Y, Güneş M, ”Investigation of The Success of Particle Swarm Optimization Based PID Classic PID and Fuzzy Type Inspection Methods in Speed Control of DC Motor”, Kahramanmaras Sutcu Imam University Journal of Engineering Sciences KSU. Journal of Engineering Sciences, 20(4), 158-167, 2017.
  • [16] Kaushal A, Thakur N, Nagaria D, “Comparison of Speed Control of DC Motor Using Fuzzy- PID and PSO-PID”, Technique International Journal of Information & Computation Technology, 4(6), 553-558, 2014.
  • [17] Ghareaghaji A, “A Comparison between Fuzzy-PSO Controller and PID-PSO Controller for Controlling a DC Motor”, Bulletin of Electrical Engineering and Informatics, 4(2), 130-135, 2015.
  • [18] El-Gammal A, El-Samahy, Adel A. “A Modified Design of PID Controller for DC Motor Drives Using Particle Swarm Optimization”, International Conference on Power Engineering, Energy and Electrical Drives, 419–424, 2009.
Toplam 18 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Seyfettin Vadi

Ramazan Bayındır

Yayımlanma Tarihi 13 Temmuz 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 2 Sayı: 1

Kaynak Göster

APA Vadi, S., & Bayındır, R. (2019). DA Motoru Kapalı Çevrim Hız Denetim Sistemindeki PI Parametrelerinin Genetik ve Parçacık Sürü Algoritması Kullanarak Optimizasyonu. Veri Bilimi, 2(1), 51-60.



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