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Ters Sarkaç Sisteminin Yapay Arı Kolonisi Algoritması ile Optimizasyonu

Year 2017, Volume: 20 Issue: 4, 863 - 868, 20.12.2017
https://doi.org/10.2339/politeknik.369045

Abstract

Bu çalışmada,
kullanımı gittikçe yaygınlaşan Yapay Arı Kolonisi Algoritması kullanılarak ters
sarkacı denetleyen Oransal-İntegral-Türevsel kontrolcünün optimizasyonu
yapılmıştır. Ters sarkacın modellenmesi ve kontrolü simülasyon ortamında
yapılmış olup, simülasyon sonucunda elde edilen veriler Yapay Arı Kolonisi
algoritmasının geleneksel yöntemlerden daha iyi ve hızlı sonuç verdiğini
göstermektedir.

References

  • [1] Blum C., “Ant Colony Optimization: Introduction and Hybridizations”, 7th International Conference on Hybrid Intelligent Systems, Kaiserlautern, Germany, 353-373, (2007). [2] Asteroth A. and Hagg A., “How to Successfully Apply Genetic Algorithms in Practice: Representation and Parametrization”, International Symposium on Innovations in Intelligent SysTems and Applications, Madrid, Spain, 1-6, (2015). [3] Marini F. and Walczak B., “Particle Swarm Optimization (PSO). A Tutorial”, Chemometrics and Intelligent Laboratory Systems, 149: 153–165, (2015). [4] Akyol S. and Alataş B., “Güncel Sürü Zekâsı Optimizasyon Algoritmaları”, Nevşehir Üniversitesi Fen Bilimleri Enstitü Dergisi, 1: 36–50, (2012). [5] Karaboga D. and Basturk B., “A Powerful and Efficient Algorithm for Numerical Function Optimization: Artificial Bee Colony (ABC) Algorithm”, Journal of Global Optimization, 39(3): 459–471, (2007). [6] Yan G. and Li C., “An Effective Refinement Artificial Bee Colony Optimization Algorithm Based on Chaotic Search and Application for PID Control Tuning”, Journal of Computational Information Systems, 7(9): 3309–3316, (2011). [7] Kumar R. and Singla S.K., “A Comparative Analysis of Different Methods for the Tuning of PID Controller”, International Journal of Electronics Communications and Electrical Engineering, 3(2): 1–17, (2013). [8] Karaboğa D., "Yapay Zeka Optimizasyon Algoritmaları", Üçüncü baskı, Nobel, Ankara, (2014). [9] Karaboga D. and Akay B., “A Survey: Algorithms Simulating Bee Swarm Intelligence”, Artificial Intelligence Review, 31(1-4): 61–85, (2009). [10] Mishra A.K., Khanna A., Singh N.K. and Mishra V.K., “Speed Control of Dc Motor Using Particle Swarm Optimization Technique”, Universal Journal of Electrical and Electronic Engineering, 1(3): 68–75, (2013). [11] Verma B.K. and Kumar D., “A review on Artificial Bee Colony Algorithm”, International Journal of Engineering and Technology, 2(3): 175–186, (2013). [12] Jain N., Gupta R. and Parmar G., “Intelligent Controlling of an Inverted Pendulum Using PSO-PID Controller”, International Journal of Engineering Research and Technology, 2(12): 3712–3716, (2013). [13] Montiel O., Sepulveda R., Melin P., Castillo O., Porta M.A. and Meza I.M., “Performance of a Simple Tuned Fuzzy Controller and a PID Controller on a DC Motor”, IEEE Symposium on Foundations of Computational Intelligence, Honolulu, Hawaii, 531-537, (2007). [14] Ziegler J.G. and Nichols N.B., “Optimum Settings for Automatic Controllers”, Journal of Dynamic Systems, Measurement, and Control, 115(2B): 759-765, (1993). [15] Khan M.R., Khan A.A. and Ghazali U., “Speed Control of DC Motor Under Varying Load Using PID Controller”, International Journal of Engineering, 9(3): 38–48, (2015). [16] Karaboga D., Gorkemli B., Ozturk C. and Karaboga N., “A Comprehensive Survey: Artificial Bee Colony (ABC) Algorithm and Applications”, Artificial Intelligence Review, 42(1): 21–57, (2014). [17] Saab S.M., El-Omari N.K.T.and Owaied H.H., “Developing Optimization Algorithm Using Artificial Bee Colony System”, Ubiquitous Computing and Communication Journal, 4(5): 15–19, (2009). [18] Campo A.B., "PID Control Design, MATLAB - A Fundamental Tool for Scientific Computing and Engineering Applications - Volume 1", InTech, (2012). [19] Hussain K.M., Zepherin R.A.R. and Kumar M.S., “Comparison of Tuning Methods of PID Controllers for FOPTD System”, International Journal of Innovative Research In Electrical, Electronics, Instrumentation and Control Engineering, 2(3): 1177–1180, (2014).
Year 2017, Volume: 20 Issue: 4, 863 - 868, 20.12.2017
https://doi.org/10.2339/politeknik.369045

Abstract

References

  • [1] Blum C., “Ant Colony Optimization: Introduction and Hybridizations”, 7th International Conference on Hybrid Intelligent Systems, Kaiserlautern, Germany, 353-373, (2007). [2] Asteroth A. and Hagg A., “How to Successfully Apply Genetic Algorithms in Practice: Representation and Parametrization”, International Symposium on Innovations in Intelligent SysTems and Applications, Madrid, Spain, 1-6, (2015). [3] Marini F. and Walczak B., “Particle Swarm Optimization (PSO). A Tutorial”, Chemometrics and Intelligent Laboratory Systems, 149: 153–165, (2015). [4] Akyol S. and Alataş B., “Güncel Sürü Zekâsı Optimizasyon Algoritmaları”, Nevşehir Üniversitesi Fen Bilimleri Enstitü Dergisi, 1: 36–50, (2012). [5] Karaboga D. and Basturk B., “A Powerful and Efficient Algorithm for Numerical Function Optimization: Artificial Bee Colony (ABC) Algorithm”, Journal of Global Optimization, 39(3): 459–471, (2007). [6] Yan G. and Li C., “An Effective Refinement Artificial Bee Colony Optimization Algorithm Based on Chaotic Search and Application for PID Control Tuning”, Journal of Computational Information Systems, 7(9): 3309–3316, (2011). [7] Kumar R. and Singla S.K., “A Comparative Analysis of Different Methods for the Tuning of PID Controller”, International Journal of Electronics Communications and Electrical Engineering, 3(2): 1–17, (2013). [8] Karaboğa D., "Yapay Zeka Optimizasyon Algoritmaları", Üçüncü baskı, Nobel, Ankara, (2014). [9] Karaboga D. and Akay B., “A Survey: Algorithms Simulating Bee Swarm Intelligence”, Artificial Intelligence Review, 31(1-4): 61–85, (2009). [10] Mishra A.K., Khanna A., Singh N.K. and Mishra V.K., “Speed Control of Dc Motor Using Particle Swarm Optimization Technique”, Universal Journal of Electrical and Electronic Engineering, 1(3): 68–75, (2013). [11] Verma B.K. and Kumar D., “A review on Artificial Bee Colony Algorithm”, International Journal of Engineering and Technology, 2(3): 175–186, (2013). [12] Jain N., Gupta R. and Parmar G., “Intelligent Controlling of an Inverted Pendulum Using PSO-PID Controller”, International Journal of Engineering Research and Technology, 2(12): 3712–3716, (2013). [13] Montiel O., Sepulveda R., Melin P., Castillo O., Porta M.A. and Meza I.M., “Performance of a Simple Tuned Fuzzy Controller and a PID Controller on a DC Motor”, IEEE Symposium on Foundations of Computational Intelligence, Honolulu, Hawaii, 531-537, (2007). [14] Ziegler J.G. and Nichols N.B., “Optimum Settings for Automatic Controllers”, Journal of Dynamic Systems, Measurement, and Control, 115(2B): 759-765, (1993). [15] Khan M.R., Khan A.A. and Ghazali U., “Speed Control of DC Motor Under Varying Load Using PID Controller”, International Journal of Engineering, 9(3): 38–48, (2015). [16] Karaboga D., Gorkemli B., Ozturk C. and Karaboga N., “A Comprehensive Survey: Artificial Bee Colony (ABC) Algorithm and Applications”, Artificial Intelligence Review, 42(1): 21–57, (2014). [17] Saab S.M., El-Omari N.K.T.and Owaied H.H., “Developing Optimization Algorithm Using Artificial Bee Colony System”, Ubiquitous Computing and Communication Journal, 4(5): 15–19, (2009). [18] Campo A.B., "PID Control Design, MATLAB - A Fundamental Tool for Scientific Computing and Engineering Applications - Volume 1", InTech, (2012). [19] Hussain K.M., Zepherin R.A.R. and Kumar M.S., “Comparison of Tuning Methods of PID Controllers for FOPTD System”, International Journal of Innovative Research In Electrical, Electronics, Instrumentation and Control Engineering, 2(3): 1177–1180, (2014).
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Details

Subjects Engineering
Journal Section Research Article
Authors

Hüseyin Oktay Erkol This is me

Publication Date December 20, 2017
Submission Date November 7, 2016
Published in Issue Year 2017 Volume: 20 Issue: 4

Cite

APA Erkol, H. O. (2017). Ters Sarkaç Sisteminin Yapay Arı Kolonisi Algoritması ile Optimizasyonu. Politeknik Dergisi, 20(4), 863-868. https://doi.org/10.2339/politeknik.369045
AMA Erkol HO. Ters Sarkaç Sisteminin Yapay Arı Kolonisi Algoritması ile Optimizasyonu. Politeknik Dergisi. December 2017;20(4):863-868. doi:10.2339/politeknik.369045
Chicago Erkol, Hüseyin Oktay. “Ters Sarkaç Sisteminin Yapay Arı Kolonisi Algoritması Ile Optimizasyonu”. Politeknik Dergisi 20, no. 4 (December 2017): 863-68. https://doi.org/10.2339/politeknik.369045.
EndNote Erkol HO (December 1, 2017) Ters Sarkaç Sisteminin Yapay Arı Kolonisi Algoritması ile Optimizasyonu. Politeknik Dergisi 20 4 863–868.
IEEE H. O. Erkol, “Ters Sarkaç Sisteminin Yapay Arı Kolonisi Algoritması ile Optimizasyonu”, Politeknik Dergisi, vol. 20, no. 4, pp. 863–868, 2017, doi: 10.2339/politeknik.369045.
ISNAD Erkol, Hüseyin Oktay. “Ters Sarkaç Sisteminin Yapay Arı Kolonisi Algoritması Ile Optimizasyonu”. Politeknik Dergisi 20/4 (December 2017), 863-868. https://doi.org/10.2339/politeknik.369045.
JAMA Erkol HO. Ters Sarkaç Sisteminin Yapay Arı Kolonisi Algoritması ile Optimizasyonu. Politeknik Dergisi. 2017;20:863–868.
MLA Erkol, Hüseyin Oktay. “Ters Sarkaç Sisteminin Yapay Arı Kolonisi Algoritması Ile Optimizasyonu”. Politeknik Dergisi, vol. 20, no. 4, 2017, pp. 863-8, doi:10.2339/politeknik.369045.
Vancouver Erkol HO. Ters Sarkaç Sisteminin Yapay Arı Kolonisi Algoritması ile Optimizasyonu. Politeknik Dergisi. 2017;20(4):863-8.