• DocumentCode
    2961593
  • Title

    Control of inverted pendulum system using a neuro-fuzzy controller for intelligent control education

  • Author

    Lee, Geun Hyeong ; Jung, Seul

  • Author_Institution
    Mechatron. Eng. Dept., Chunganm Nat. Univ., Daejeon
  • fYear
    2008
  • fDate
    5-8 Aug. 2008
  • Firstpage
    965
  • Lastpage
    970
  • Abstract
    This article presents the implementation of control of an inverted pendulum system by using the neuro-fuzzy network. The inverted pendulum system has been built in the educational kit whose purpose is to educate control engineers in both undergraduate students and graduate students. The inverted pendulum system is known as a nonlinear system whose goal is to maintain the balance of the pendulum while tracking a desired position of the cart. The Takagi-Sugeno (T-S) neuro-fuzzy control scheme is used to control the system. The back-propagation learning algorithm for the T-S neuro-fuzzy network is derived for on-line learning and control. The control algorithm has been embedded on a DSP 2812 board to achieve the real-time control performance. Experimental results show that successful control performances of both balancing and tracking the position for the inverted pendulum system.
  • Keywords
    backpropagation; control engineering education; fuzzy control; fuzzy neural nets; intelligent control; learning (artificial intelligence); neurocontrollers; nonlinear control systems; DSP 2812 board; Takagi-Sugeno neuro-fuzzy control scheme; backpropagation learning algorithm; graduate students; intelligent control education; inverted pendulum system; nonlinear system; undergraduate students; Adaptive control; Communication system control; Control systems; Fuzzy logic; Fuzzy neural networks; Intelligent control; Intelligent robots; Mechatronics; Neural networks; Programmable control; Neuro-fuzzy controller; intelligent control education; inverted pendulum;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Automation, 2008. ICMA 2008. IEEE International Conference on
  • Conference_Location
    Takamatsu
  • Print_ISBN
    978-1-4244-2631-7
  • Electronic_ISBN
    978-1-4244-2632-4
  • Type

    conf

  • DOI
    10.1109/ICMA.2008.4798889
  • Filename
    4798889