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AKILLI SİSTEMLER VE UYGULAMALARI DERGİSİ
JOURNAL OF INTELLIGENT SYSTEMS WITH APPLICATIONS
J. Intell. Syst. Appl.
E-ISSN: 2667-6893
Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.

Control of Inverted Pendulum Using Fractional Order PID Controllers Based on Particle Swarm Optimization

Parçacık Sürüsü Optimizasyonu Kullanılarak Ters Sarkaç Sisteminin Kesir Dereceli PID ile Kontrolü

How to cite: Macit C, Ataşlar Ayyıldız B. Control of inverted pendulum using fractional order pid controllers based on particle swarm optimization. Akıllı Sistemler ve Uygulamaları Dergisi (Journal of Intelligent Systems with Applications) 2018; 1(2): 98-102. DOI: 10.54856/jiswa.201812031

Full Text: PDF, in Turkish.

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Title: Control of Inverted Pendulum Using Fractional Order PID Controllers Based on Particle Swarm Optimization

Abstract: Issue of balance in robotics is best represented by the balancing act of the inverted pendulums. With their unstable and nonlinear behaviour, Inverted Pendulum systems are quite popular systems in which various control design methods are applied and performance comparisons are carried out. In this study, in order to control the pendulum angle and car position of the inverted pendulum system, a fractional order PID controller is designed. Gains of the designed controller are optimized by Particle Swarm Optimization method. On the other hand, for the aim of comparison of performance, conventional PID controllers are used for controllers. The optimum values of gains for PID controllers are also found by same optimization algorithm. The simulation results of both controllers are compared for the inverted pendulum.

Keywords: Inverted pendulum; fractional order PID; particle swarm optimization


Başlık: Parçacık Sürüsü Optimizasyonu Kullanılarak Ters Sarkaç Sisteminin Kesir Dereceli PID ile Kontrolü

Özet: Robotik alanında yapılan bilimsel çalışmalarda, denge konusunu en iyi temsil eden örnek ters sarkacın denge hareketidir. Bu sebeple, kararsız ve doğrusal olmayan yapısıyla ters sarkaç sistemleri, kontrol tasarım yöntemlerinin uygulandığı ve performans karşılaştırmasının yapıldığı başlıca sistemlerden biridir. Bu çalışmada, ters sarkaç sisteminde yer alan sarkaç ve araç konumunu kontrol etmek için Parçacık Sürüsü Optimizasyon (PSO) algoritması ile optimize edilen kesir dereceli PID kontrolör tasarımı yapılmıştır. Ayrıca, önerilen kontrolörün performansını test etmek amacıyla, aynı optimizasyon algoritması kullanılarak PID kontrolör tasarlanmıştır. Tasarımı yapılan kontrolörler için kontrol sonuçları simülasyonlarla elde edilerek, grafiksel olarak ters sarkaç sistemi üzerinde performansları karşılaştırılmıştır.

Anahtar kelimeler: Ters sarkaç sistemi; kesir dereceli PID; parçacık sürüsü optimizasyonu


Bibliography:
  • Wang JJ. Simulation studies of inverted pendulum based on PID controllers. Simulation Modelling Practice and Theory 2011; 19(1): 440–449.
  • Jia-Jun W. Position and speed tracking control of inverted pendulum based on double PID controllers. In 34th Chinese Control Conference (CCC), July 28-30, 2015, Hangzhou, China, pp. 4197-4201.
  • Razzaghi K, Jalali AA. A new approach on stabilization control of an inverted pendulum, using PID controller. In 2011 International Conference on Control, Robotics and Cybernetics, March 19-21, 2011, New Delhi, India, pp. VI-81-VI-85.
  • Yazici A, Karamancioglu A. Ters sarkac sisteminin kontrol egitiminde test araci olarak kullanilmasi. Elektrik Elektronik Bilgisayar Biyomedikal Mühendislikleri Egitimi IV. Ulusal Sempozyumu, October 22-24, 2009, Eskisehir, Turkey.
  • Kumar V, Jeromeb J. Robust LQR controller design for stabilizing and trajectory tracking of inverted pendulum. Procedia Engineering 2013; 64: 169–178.
  • Yuce A, Tan N. Ters sarkac sistemi icin lag/lead kontrolor tasarimi. Otomatik Kontrol Ulusal Toplantısı (TOK 2013), September 26-28, 2013, Malatya, Turkey, pp. 303–308.
  • Sukontanakarn V, Parnichkun M. Real-time optimal control for rotary inverted pendulum. American Journal of Applied Sciences 2009; 6(6): 1106–1115.
  • Khanesar MA, Teshnehlab M, Shoorehdeli MA. Sliding mode control of rotary inverted pendulum. In 15th Mediterranean Conference on Control and Automation, June 27-29, 2007, Athens, Greece.
  • Kizir S. Development and control of the nonlinear inverted pendulum system. MSc Thesis, Kocaeli University, 2008.
  • Horikawa S, Yamaguchi M, Furuhashi T, Uchikawa Y. Fuzzy control for inverted pendulum using fuzzy neural networks. Journal of Robotics and Mechatronics 1995; 7(1): 36–44.
  • Zadeh IH, Mobayen S. PSO-based controller for balancing rotary inverted pendulum. Journal of Applied Sciences 2008; 8(16): 2907–2912.
  • Nour MIH, Ooi J, Chan KY. Fuzzy logic control vs. conventional PID control of an inverted pendulum robot. In International Conference on Intelligent and Advanced Systems, November 25-28, 2007, Kuala Lumpur, Malaysia, pp. 209–214.
  • Khosla A, Leena G, Soni MK. Interval type-2 fuzzy logic controller to control the velocity and angle of inverted pendulum. International Journal of Intelligent Systems and Applications 2014; 6(7): 44-51.
  • Ortigueira MD. Fractional Calculus for Scientists and Engineers. Springer, Berlin, Germany, 2011.
  • Xue DY, and Chen YQ. A comparative introduction of four fractional order controllers. In 4th World Congress on Intelligent Control and Automation, June 10-14, 2002, Shanghai, China, pp. 3228–3235.
  • Podlubny I. Fractional-order systems and PID controllers. IEEE Transactions on Automatic Control 1999; 44(1): 208–214.
  • Oustaloup A. La commande CRONE: commande robuste d'ordre non entire. Hermes, Traite des nouvelles technologies. Serie automatique, Paris, France, 1991.
  • Oustaloup A, Levron F, Mathieu B, Nanot FM. Frequency-band complex noninteger differentiator: Characterization and synthesis. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 2000; 47(1): 25–39.
  • Valerio D, da Costa JS. Time-domain implementation of fractional order controllers. IEE Proceedings Control Theory and Applications 2005; 152(5): 539–552.
  • Kennedy J, Eberhart RC. Particle swarm optimization. In IEEE International Conference on Neural Networks, November 27-December 1, 1995, Perth, WA, Australia, pp. 1942–1948, 1995.