Araştırma Makalesi
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İki serbestlik dereceli bir robot kolun konum kontrolü için PID kontrol parametrelerinin arı algoritması (AA) kullanılarak belirlenmesi

Yıl 2022, , 111 - 124, 05.01.2022
https://doi.org/10.25092/baunfbed.885152

Öz

Bu çalışmada, bir robot kolun konum kontrolü için PID kontrol parametreleri Genetik algoritma (GA) ve Arı Algoritması (AA) kullanılarak belirlenmiştir. Robot kolun dinamik ve kinematik denklemleri elde edilerek matematiksel modeli oluşturulmuştur. GA ve AA ile PID kontrol parametreleri belirlenirken minimum konum hatası sağlanabilmesi amaçlanmıştır. Optimizasyon ve benzetim çalışmaları Matlab/Simulink ortamında yapılmıştır ve elde edilen sonuçlardan; Her iki algoritmasının da PID kontrol parametrelerinin belirlenmesinde başarılı olduğu ve robot kolun istenilen referans konumlara gelebildiği görülmüştür. Ancak, Arı Algoritması ile elde edilen sonuçlarda daha az maksimum aşmalar gözlenmiştir.

Kaynakça

  • Berg, A., Buffie, E. F., and Zanna, L.-F., Robots, growth, and inequality, Finance & Development, 53, 3, 10-13, (2016).
  • Enescu, M. L. and Alexandru, C., Modeling and simulation of a 6 DOF robot, Advanced Materials Research, 463, 1116-1119, (2012).
  • Kim, H.-S. and Song, J.-B., Low-cost robot arm with 3-DOF counterbalance mechanism, 2013 IEEE International Conference on Robotics and Automation, 4183-4188, Karlsruhe, (2013).
  • S. Klug, O. von Stryk and B. Mohl, Design and Control Mechanisms for a 3 DOF Bionic Manipulator, The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2006., 450-454, Pisa, (2006).
  • Wu, J., Wang, J., Li, T., and Wang, L., Analysis and application of a 2-DOF planar parallel mechanism, Journal of Mechanical Design, 129, 4, 434–437, (2007).
  • Amer, A. F., Sallam, E. A., and Elawady, W. M., Adaptive fuzzy sliding mode control using supervisory fuzzy control for 3 DOF planar robot manipulators, Applied Soft Computing, 11, 8, 4943-4953, (2011).
  • Çakan, A. and Botsali, F. M., Inverse kinematics analysis of a puma robot by using MSC Adams, VI International Conference Industrial Engineering and Environmental Protection, 274-277, Zrenjanin, (2016).
  • Spong, M. W., Hutchinson, S., and Vidyasagar, M., Robot modeling and control, John Wiley & Sons, (2006).
  • Cervantes, I. and Alvarez-Ramirez, J., On the PID tracking control of robot manipulators, Systems & Control Letters, 42, 1, 37-46, (2001).
  • İlgen, S., Durdu, A., Gülbahçe, E., and Çakan, A., İki Linkli Robot Manipülatörün Modellenmesi ve Bozucu Etki Altında Yörünge Kontrolü, 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 1-5, Istanbul, (2020).
  • ÖNEN, Ü., Cakan, A., and Ilhan, I., Performance comparison of optimization algorithms in LQR controller design for a nonlinear system, Turkish Journal of Electrical Engineering & Computer Sciences, 27, 3, 1938-1953, (2019).
  • KILIÇ, F., BİCAKCI, S., and Güneş, H., Ters sarkacın uyarlamalı kazançlı bağımsız yüzeyli kayan kip yöntemi ile denetimi, Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 21, 2, 610-622, (2019).
  • Lochan, K. and Roy, B., Control of two-link 2-dof robot manipulator using fuzzy logic techniques: A review, 4th International Conference on Soft Computing for Problem Solving, 335, 499-511, New Delhi, (2015).
  • Ogata, K., Modern control engineering. Prentice hall, (2010).
  • Çalgan, H., Yaman, R., İlten, E., and Demirtaş, M., Fırçasız DA motorunun hız kontrolünde PI katsayılarının Pareto tabanlı çok amaçlı optimizasyonu, Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 20, 2, 330-346, (2018).
  • Civelek, Z., Optimization of fuzzy logic (Takagi-Sugeno) blade pitch angle controller in wind turbines by genetic algorithm, Engineering Science and Technology, an International Journal, 23, 1, 1-9, (2020).
  • Liang, H., Zou, J., Zuo, K., and Khan, M. J., An improved genetic algorithm optimization fuzzy controller applied to the wellhead back pressure control system, Mechanical Systems and Signal Processing, 142, 106708, (2020).
  • Solihin, M. I., Tack, L. F., and Kean, M. L., Tuning of PID controller using particle swarm optimization (PSO), International Journal on Advanced Science, Engineering and Information Technology, 1, 4, 458-461, (2011).
  • Oshaba, A. S., Ali, E. S., and Abd Elazim, S. M., "PI controller design using ABC algorithm for MPPT of PV system supplying DC motor pump load, Neural Computing and Applications, 28, 2, 353-364, (2015).
  • Karaboga, D. and Akay, B., "Proportional—integral—derivative controller design by using artificial bee colony, harmony search, and the bees algorithms, Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 224, 7, 869-883, (2010).
  • Mustafa, A. M. and Al-Saif, A., Modeling, simulation and control of 2-R robot, Global Journal of Research In Engineering, 14, 1H, (2014).
  • Kucuk, S. and Bingul, Z., Robot kinematics: Forward and inverse kinematics. INTECH Open Access Publisher, (2006).
  • Ang, K. H., Chong, G., and Li, Y., PID control system analysis, design, and technology, IEEE Transactions on Control Systems Technology, 13, 4, 559-576, (2005).
  • Pham, D.T., Koç, E., Ghanbarzadeh, A., Otri, S., Rahim,S., Zaidi, M., The Bees Algorithm A Novel Tool for Complex Optimisation Problems, 2nd International Virtual Conference on Intelligent Production Machines and Systems, 454-461, (2006).
  • Karaboga, D., An idea based on honey bee swarm for numerical optimization, Citeseer, (2005).
  • Karaboga, D. and Akay, B., "A comparative study of artificial bee colony algorithm," Applied Mathematics and Computation, 214, 1, 108-132, (2009).
  • 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).
  • Karaboga, D. and Basturk, B., On the performance of artificial bee colony (ABC) algorithm, Applied soft computing, 8, 1, 687-697, (2008).
  • Pham, D.T., Koç, E., Kalyoncu, M., Tınkır, M., Hierarchical PID Controller Design for a Flexible Link Robot Manipulator Using the Bees Algorithm, 6th International Symposium on Intelligent Manufacturing Systems, 757-765, Sakarya, (2008).
  • Pham, D. and Kalyoncu, M., Optimisation of a fuzzy logic controller for a flexible single-link robot arm using the Bees Algorithm, 7th IEEE International Conference on Industrial Informatics, 475-480, (2009).
  • Bakırcıoğlu, V., Şen, M., and Kalyoncu, M., Dört Ayaklı Robotun Bir Bacağı İçin PID Kontrolcü Tasarımı ve Arı Algoritması Kullanarak Optimizasyonu, Uluslararası Katılımlı 17. Makina Teorisi Sempozyumu, İzmir, (2015).
  • Arif Şen, M., Tinkir, M., and Kalyoncu, M., Optimisation of a PID controller for a two-floor structure under earthquake excitation based on the bees algorithm, Journal of Low Frequency Noise, Vibration and Active Control, 37, 1, 107-127, (2018).
  • Şen, M. A., Bakırcıoğlu, V., and Kalyoncu, M., Performances Comparison of The Bees Algorithm and Genetic Algorithm for PID Controller Tuning, 5th International Conference on Mechatronics and Control Engineering - ICMCE '16, (2016).
  • Sen, M. A. and Kalyoncu, M., Optimisation of a PID Controller for an Inverted Pendulum Using the Bees Algorithm, Applied Mechanics and Materials, 789-790, 1039-1044, (2015).

Determination of PID control parameters for position control of a 2-dof robot arm using the bees algorithm (BA)

Yıl 2022, , 111 - 124, 05.01.2022
https://doi.org/10.25092/baunfbed.885152

Öz

In this study, PID control parameters for position control of a robot arm were determined using Genetic Algorithm (GA) and The Bees Algorithm (BA). The mathematical model of the robot arm is created by obtaining the dynamic and kinematic equations. While determining PID control parameters with GA and BA, it is aimed to provide minimum position error. Optimization and simulation studies is realized in Matlab/Simulink environment and the results are shown that both algorithms are successful in determining the PID control parameters and the robot arm can reach the desired reference positions. However, less maximum overshoots are observed in the results obtained with The Bees Algorithm.

Kaynakça

  • Berg, A., Buffie, E. F., and Zanna, L.-F., Robots, growth, and inequality, Finance & Development, 53, 3, 10-13, (2016).
  • Enescu, M. L. and Alexandru, C., Modeling and simulation of a 6 DOF robot, Advanced Materials Research, 463, 1116-1119, (2012).
  • Kim, H.-S. and Song, J.-B., Low-cost robot arm with 3-DOF counterbalance mechanism, 2013 IEEE International Conference on Robotics and Automation, 4183-4188, Karlsruhe, (2013).
  • S. Klug, O. von Stryk and B. Mohl, Design and Control Mechanisms for a 3 DOF Bionic Manipulator, The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob 2006., 450-454, Pisa, (2006).
  • Wu, J., Wang, J., Li, T., and Wang, L., Analysis and application of a 2-DOF planar parallel mechanism, Journal of Mechanical Design, 129, 4, 434–437, (2007).
  • Amer, A. F., Sallam, E. A., and Elawady, W. M., Adaptive fuzzy sliding mode control using supervisory fuzzy control for 3 DOF planar robot manipulators, Applied Soft Computing, 11, 8, 4943-4953, (2011).
  • Çakan, A. and Botsali, F. M., Inverse kinematics analysis of a puma robot by using MSC Adams, VI International Conference Industrial Engineering and Environmental Protection, 274-277, Zrenjanin, (2016).
  • Spong, M. W., Hutchinson, S., and Vidyasagar, M., Robot modeling and control, John Wiley & Sons, (2006).
  • Cervantes, I. and Alvarez-Ramirez, J., On the PID tracking control of robot manipulators, Systems & Control Letters, 42, 1, 37-46, (2001).
  • İlgen, S., Durdu, A., Gülbahçe, E., and Çakan, A., İki Linkli Robot Manipülatörün Modellenmesi ve Bozucu Etki Altında Yörünge Kontrolü, 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 1-5, Istanbul, (2020).
  • ÖNEN, Ü., Cakan, A., and Ilhan, I., Performance comparison of optimization algorithms in LQR controller design for a nonlinear system, Turkish Journal of Electrical Engineering & Computer Sciences, 27, 3, 1938-1953, (2019).
  • KILIÇ, F., BİCAKCI, S., and Güneş, H., Ters sarkacın uyarlamalı kazançlı bağımsız yüzeyli kayan kip yöntemi ile denetimi, Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 21, 2, 610-622, (2019).
  • Lochan, K. and Roy, B., Control of two-link 2-dof robot manipulator using fuzzy logic techniques: A review, 4th International Conference on Soft Computing for Problem Solving, 335, 499-511, New Delhi, (2015).
  • Ogata, K., Modern control engineering. Prentice hall, (2010).
  • Çalgan, H., Yaman, R., İlten, E., and Demirtaş, M., Fırçasız DA motorunun hız kontrolünde PI katsayılarının Pareto tabanlı çok amaçlı optimizasyonu, Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 20, 2, 330-346, (2018).
  • Civelek, Z., Optimization of fuzzy logic (Takagi-Sugeno) blade pitch angle controller in wind turbines by genetic algorithm, Engineering Science and Technology, an International Journal, 23, 1, 1-9, (2020).
  • Liang, H., Zou, J., Zuo, K., and Khan, M. J., An improved genetic algorithm optimization fuzzy controller applied to the wellhead back pressure control system, Mechanical Systems and Signal Processing, 142, 106708, (2020).
  • Solihin, M. I., Tack, L. F., and Kean, M. L., Tuning of PID controller using particle swarm optimization (PSO), International Journal on Advanced Science, Engineering and Information Technology, 1, 4, 458-461, (2011).
  • Oshaba, A. S., Ali, E. S., and Abd Elazim, S. M., "PI controller design using ABC algorithm for MPPT of PV system supplying DC motor pump load, Neural Computing and Applications, 28, 2, 353-364, (2015).
  • Karaboga, D. and Akay, B., "Proportional—integral—derivative controller design by using artificial bee colony, harmony search, and the bees algorithms, Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 224, 7, 869-883, (2010).
  • Mustafa, A. M. and Al-Saif, A., Modeling, simulation and control of 2-R robot, Global Journal of Research In Engineering, 14, 1H, (2014).
  • Kucuk, S. and Bingul, Z., Robot kinematics: Forward and inverse kinematics. INTECH Open Access Publisher, (2006).
  • Ang, K. H., Chong, G., and Li, Y., PID control system analysis, design, and technology, IEEE Transactions on Control Systems Technology, 13, 4, 559-576, (2005).
  • Pham, D.T., Koç, E., Ghanbarzadeh, A., Otri, S., Rahim,S., Zaidi, M., The Bees Algorithm A Novel Tool for Complex Optimisation Problems, 2nd International Virtual Conference on Intelligent Production Machines and Systems, 454-461, (2006).
  • Karaboga, D., An idea based on honey bee swarm for numerical optimization, Citeseer, (2005).
  • Karaboga, D. and Akay, B., "A comparative study of artificial bee colony algorithm," Applied Mathematics and Computation, 214, 1, 108-132, (2009).
  • 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).
  • Karaboga, D. and Basturk, B., On the performance of artificial bee colony (ABC) algorithm, Applied soft computing, 8, 1, 687-697, (2008).
  • Pham, D.T., Koç, E., Kalyoncu, M., Tınkır, M., Hierarchical PID Controller Design for a Flexible Link Robot Manipulator Using the Bees Algorithm, 6th International Symposium on Intelligent Manufacturing Systems, 757-765, Sakarya, (2008).
  • Pham, D. and Kalyoncu, M., Optimisation of a fuzzy logic controller for a flexible single-link robot arm using the Bees Algorithm, 7th IEEE International Conference on Industrial Informatics, 475-480, (2009).
  • Bakırcıoğlu, V., Şen, M., and Kalyoncu, M., Dört Ayaklı Robotun Bir Bacağı İçin PID Kontrolcü Tasarımı ve Arı Algoritması Kullanarak Optimizasyonu, Uluslararası Katılımlı 17. Makina Teorisi Sempozyumu, İzmir, (2015).
  • Arif Şen, M., Tinkir, M., and Kalyoncu, M., Optimisation of a PID controller for a two-floor structure under earthquake excitation based on the bees algorithm, Journal of Low Frequency Noise, Vibration and Active Control, 37, 1, 107-127, (2018).
  • Şen, M. A., Bakırcıoğlu, V., and Kalyoncu, M., Performances Comparison of The Bees Algorithm and Genetic Algorithm for PID Controller Tuning, 5th International Conference on Mechatronics and Control Engineering - ICMCE '16, (2016).
  • Sen, M. A. and Kalyoncu, M., Optimisation of a PID Controller for an Inverted Pendulum Using the Bees Algorithm, Applied Mechanics and Materials, 789-790, 1039-1044, (2015).
Toplam 34 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Araştırma Makalesi
Yazarlar

Erdem Karakoyun 0000-0002-5419-7430

Abdullah Çakan 0000-0003-3923-4069

Mete Kalyoncu 0000-0002-2214-7631

Yayımlanma Tarihi 5 Ocak 2022
Gönderilme Tarihi 22 Şubat 2021
Yayımlandığı Sayı Yıl 2022

Kaynak Göster

APA Karakoyun, E., Çakan, A., & Kalyoncu, M. (2022). İki serbestlik dereceli bir robot kolun konum kontrolü için PID kontrol parametrelerinin arı algoritması (AA) kullanılarak belirlenmesi. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 24(1), 111-124. https://doi.org/10.25092/baunfbed.885152
AMA Karakoyun E, Çakan A, Kalyoncu M. İki serbestlik dereceli bir robot kolun konum kontrolü için PID kontrol parametrelerinin arı algoritması (AA) kullanılarak belirlenmesi. BAUN Fen. Bil. Enst. Dergisi. Ocak 2022;24(1):111-124. doi:10.25092/baunfbed.885152
Chicago Karakoyun, Erdem, Abdullah Çakan, ve Mete Kalyoncu. “İki Serbestlik Dereceli Bir Robot Kolun Konum Kontrolü için PID Kontrol Parametrelerinin Arı Algoritması (AA) kullanılarak Belirlenmesi”. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi 24, sy. 1 (Ocak 2022): 111-24. https://doi.org/10.25092/baunfbed.885152.
EndNote Karakoyun E, Çakan A, Kalyoncu M (01 Ocak 2022) İki serbestlik dereceli bir robot kolun konum kontrolü için PID kontrol parametrelerinin arı algoritması (AA) kullanılarak belirlenmesi. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi 24 1 111–124.
IEEE E. Karakoyun, A. Çakan, ve M. Kalyoncu, “İki serbestlik dereceli bir robot kolun konum kontrolü için PID kontrol parametrelerinin arı algoritması (AA) kullanılarak belirlenmesi”, BAUN Fen. Bil. Enst. Dergisi, c. 24, sy. 1, ss. 111–124, 2022, doi: 10.25092/baunfbed.885152.
ISNAD Karakoyun, Erdem vd. “İki Serbestlik Dereceli Bir Robot Kolun Konum Kontrolü için PID Kontrol Parametrelerinin Arı Algoritması (AA) kullanılarak Belirlenmesi”. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi 24/1 (Ocak 2022), 111-124. https://doi.org/10.25092/baunfbed.885152.
JAMA Karakoyun E, Çakan A, Kalyoncu M. İki serbestlik dereceli bir robot kolun konum kontrolü için PID kontrol parametrelerinin arı algoritması (AA) kullanılarak belirlenmesi. BAUN Fen. Bil. Enst. Dergisi. 2022;24:111–124.
MLA Karakoyun, Erdem vd. “İki Serbestlik Dereceli Bir Robot Kolun Konum Kontrolü için PID Kontrol Parametrelerinin Arı Algoritması (AA) kullanılarak Belirlenmesi”. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, c. 24, sy. 1, 2022, ss. 111-24, doi:10.25092/baunfbed.885152.
Vancouver Karakoyun E, Çakan A, Kalyoncu M. İki serbestlik dereceli bir robot kolun konum kontrolü için PID kontrol parametrelerinin arı algoritması (AA) kullanılarak belirlenmesi. BAUN Fen. Bil. Enst. Dergisi. 2022;24(1):111-24.