Anti-Swing and Position Control of Double Inverted Pendulum (DIP) on Cart Using Hybrid Neuro-Fuzzy Controllers

Anti-Swing and Position Control of Double Inverted Pendulum (DIP) on Cart Using Hybrid Neuro-Fuzzy Controllers

Автор: Ashwani Kharola

Журнал: International Journal of Information Technology and Computer Science(IJITCS) @ijitcs

Статья в выпуске: 7 Vol. 8, 2016 года.

Бесплатный доступ

This paper illustrates a comparison study for control of highly non-linear Double Inverted Pendulum (DIP) on cart. A Matlab-Simulink model of DIP has been built using Newton's second law. The Neuro-fuzzy controllers stabilizes pendulums at vertical position while cart moves in horizontal direction. This study proposes two soft-computing techniques namely Fuzzy logic reasoning and Neural networks (NN's) for control of DIP systems. The results shows that Fuzzy controllers provides better results as compared to NN's controllers in terms of settling time (sec), maximum overshoot (degree) and steady state error. The regression (R) and mean square error (MSE) values obtained after training of Neural network were satisfactory. The simulation results proves the validity of proposed techniques.

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DIP, MF's, Fuzzy logic reasoning, Neural networks, MSE, Matlab, Simulink, FLC's

Короткий адрес: https://sciup.org/15012506

IDR: 15012506

Список литературы Anti-Swing and Position Control of Double Inverted Pendulum (DIP) on Cart Using Hybrid Neuro-Fuzzy Controllers

  • C.C Lee, "Fuzzy Logic Control Systems: Fuzzy Logic Controller -Part I & II", IEEE Transactions on Systems, Man and Cybernetics, 20(2), pp. 403-435, 1990.
  • M.M. Gupta and C.J. Qi, "Fusion of Fuzzy logic and Neural Network with Application to Decision and Control Problems", In Proc. of IEEE American Control conference, pp. 30-31, 26-28 June 1991, Bostan, MA, USA.
  • N.S. Bhangal, "Design and Performance of LQR and LQR based Fuzzy controller for Double Inverted Pendulum system", Journal of Image and Graphics, 1(3), pp. 143-146, doi: 10.12720/joig.1.3.143-146, 2013
  • W. Chen, Q. Li, and R. Gu, "Chaos optimization neural network control for the stability of double inverted pendulum", In Proc. of 2nd IEEE International conference on Industrial Mechatronics and Automation (ICIMA), pp. 491-494, 30-31 May 2010, Wuhan, China.
  • Y. Xiu-fen, D. Hai-bin, and G. Hua-jun, "Research for Inverted Pendulum control based on BP Algorithm of ANN", Measurement and Control Technique, 22(3), pp. 41-44, 2003.
  • J. Yu, L. Huang, and S. Zhou, "Fuzzy control of Linear flexible Double Inverted Pendulum system", In Proc. of IEEE International Conference on Control Engineering and Communication Technology (ICCECT), 7-9 Dec. 2012, Liaoning, pp. 342-345, doi: 10.1109/ICCECT.2012.48.
  • M. Yi-Jen, and L.C. Min, "Double Inverted pendulum decoupling control by adaptive terminal sliding mode recurrent fuzzy neural network", Journal of Intelligent and Fuzzy systems, 26(4), pp. 1723-1729, doi: 10.3233/IFS-130851, 2014.
  • T. Fujinaka, Y. Kishida, M. Yoshioka, and S. Omatu, "Stabilization of Double Inverted Pendulum with Self-tuning Neuro PID", In Proc. of IEEE International Joint conference on Neural Networks (IJCNN), pp. 43-45, 24-27 July 2000.
  • Y. Sang, Y. Fan, and B. Liu, "Double Inverted Pendulum control based on three loop PID and improved BP neural network", In Proc. of 2nd IEEE International conference on Digital Manufacturing and Automation (ICDMA), pp. 456-459, 7 Aug 2011, Zhangjiajie, Hunan.
  • A. Nejafard, M.J. Yazdanpanch, and I. Hassanzadeh, "Friction compensation of double inverted pendulum on a cart using locally linear neuro-fuzzy model", Neural Computing and Applications, 22(2), pp. 337-347, doi: 10.1007/s00521-011-0686-3, 2011.
  • Y. Sang, Y. Fan, and D. Liu, "Double Inverted Pendulum control based on three-loop PID and improved BP Neural network", In Proc. of IEEE 2nd International Conference on Digital Manufacturing and Automation (ICDMA), 5-7 Aug. 2011, Zhangjiajie, Hunan, pp. 456-459, doi: 10.1109/ICDMA.2011.118.
  • S. Jung, H.T. Cho, and T.C. Hsia, "Neural network control for position tracking of a two-axis Inverted Pendulum system: Experimental studies", IEEE Transactions on Neural Networks, 18(4), pp. 1042-1048, doi: 10.1109/TNN.2007.8991-28, 2007
  • F. Cheng, G. Zhong, Y. Li, and Z. Xu, "Fuzzy control of Double inverted pendulum", Fuzzy Sets and Systems, 79(3), pp. 315-321,doi:10.1016/0165-0114(95)00156-5, 1996.
  • G.H. Lee, and S. Jung, "Control of Inverted Pendulum system using a Neuro-fuzzy controller for Intelligent control education", In Proc. of IEEE International conference on Mechatronics and Automation (ICMA), pp. 965-970, 5-8 Aug 2008, Takamatsu.
  • J. Xiao, S. Zhang, J. Xiao, and N. Xi, "Motion mode control in Double Inverted Pendulum system", In Proc. of IEEE International Conference on Advanced Intelligent Mechatronics", 24-28 July 2008, pp. 831-836, Monterey, CA, doi: 10.1109/AIM.2005.1511112.
  • S. Qianlai, and S. Zhiyi, "Application of Multistage Fuzzy Control to Double Inverted Pendulum", In Proc. IEEE International Conference on Control and Automation (ICCA), pp. 2027-2030, December 9-11, 2009, Christchurch, New Zealand.
  • M. Nalavade, M.J. Bhagat, and V.V. Patil, "Balancing Double Inverted Pendulum on cart by Linearization Technique", International Journal of Recent Technology and Engineering (IJRTE), 3(1),pp. 153-157, 2014.
  • C.W. Ji, F. Lei, L.K. Kin, "Fuzzy logic controller for an inverted pendulum system", In Proc. of IEEE International Conference on Intelligent Processing Systems, 28-31 Oct. 1997, Beijing, pp 185-189, doi: 10.1109/ICIPS.1997.672762.
  • Y. Liu, Z. Chen, D. Xue, and X. Xu, "Real-time controlling of inverted pendulum by fuzzy logic", In Proc. of IEEE International Conference on Automation and Logistics, 5-7 Aug. 2009, Shenyang, pp 1180-1183, doi: 10.1109/ICAL.2009.5262618.
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