International Journal of Control, Automation, and Systems

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Decoupled Neural Network Reference Compensation Technique for a PD Controlled Two Degrees-of-Freedom Inverted Pendulum

  • Seul Jung (Department of Mechatronics Engineering, Chungnam National University) ;
  • Cho, Hyun-Taek (Department of Mechatronics Engineering, Chungnam National University)
  • Published : 2004.03.01
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Abstract

In this paper, the decoupled neural network reference compensation technique (DRCT) is applied to the control of a two degrees-of-freedom inverted pendulum mounted on an x-y table. Neural networks are used as auxiliary controllers for both the x axis and y axis of the PD controlled inverted pendulum. The DRCT method known to compensate for uncertainties at the trajectory level is used to control both the angle of a pendulum and the position of a cart simultaneously. Implementation of an on-line neural network learning algorithm has been implemented on the DSP board of the dSpace DSP system. Experimental studies have shown successful balancing of a pendulum on an x-y plane and good position control under external disturbances as well.

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References

  1. Proc. of IEEE Conf on Knowledge Based Intelligent Electronics Systems Neuro-control for single-input multi-output systems S. Omatu;Y. Kishida;M. Yoshioka
  2. Proc. of IEEE Conf. on Robotics and Automations Swing up control of the acrobat M. W. Spong
  3. Non-linear Control for Under-actuated Mechanical Systems I. Fantoni;R. Lozano
  4. International Symposium on Robotics and Automations Reference compensation technique using neural network for controlling a large x-y table robot S. Jung;S. B. Yim
  5. IEEE Conference Neuro-pid control for inverted single and double pendulums S. Omatu;T. Fujinaka;M. Yoshioka
  6. ICASE journal of Control, Automation and Systems Engineering Experimental studies of neural network control for nonlinear systems S. Jung;S. B. Yim
  7. Proc. of IEEE Southeastcon '94 Cart-pendulum balancing problem using fuzzy logic control T. Lahdhiri;C. Camaland;A. T. Alouani
  8. Proc. of IEEE Conference on Intelligent Processing Systems A PI-like fuzzy controller implementation for the inverted pendulum system T. Hung;M. Yeh;H. C. Lu
  9. IEEE Trans. on Education v.41 no.2 Fuzzy logic control of an inverted pendulum with vision feedback M. E. Magana;F. Holzapfel https://doi.org/10.1109/13.669727
  10. Proc. of IEEE Conference on Instrumentation and Measurement Technology v.3 Computer vision based inverted pendulum L. Wenzel;N. Vazquez;ND. N. Jamal
  11. Robotica v.15 On an effective design approach of cartesian space neural network control of robot manipulators S. Jung;T. C. Hsia https://doi.org/10.1017/S0263574797000349
  12. Robotica v.19 no.3 Neural network inverse control techniques for PD controlled robot manipulators S. Jung;T. C. Hsia
  13. Robotica v.19 no.3 Neural network inverse control techniques for PD controlled robot manipulators S. Jung;T. C. Hsia