International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Design of a Fuzzy Logic Controller for a Rotary-type Inverted Pendulum System

  • Park, Byung-Jae (School of Computer and Communication Engineering, Daegu University Kyungsan Kyungpook,712-714) ;
  • Ryu, Chun-ha (School of Electrical Engineering and Computer Scienc, Kyungpook National University Daegu 702-701) ;
  • Choi, Bong-Yeol (School of Electrical Engineering and Computer Scienc, Kyungpook National University Daegu 702-701,Korea)
  • Published : 2002.06.01
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Abstract

Various inverted pendulum systems have been frequently used as a model for the performance test of the proposed control system. We first identify a rotary-type inverted pendulum system by the Euler-Lagrange method and then design a FLC (Fuzzy Logic Controller) fur the plant. FLC`s are one of useful control schemes fur plants having difficulties in deriving mathematical models or having performance limitations with conventional linear control schemes. Many FLC`s imitate the concept of conventional PD (Proportional-Derivative) or PI (Proportional-Integral) controller. That is, the error e and the change-of-error are used as antecedent variables and the control input u the change of control input Au is used as its consequent variable for FLC`s. In this paper we design a simple-structured FLC for the rotary inverted pendulum system. We also perform some computer simulations to examine the tracking performance of the closed-loop system.

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References

  1. D. Driankov, H. Hellendoom, and M. Rainfank, An Introduction to Fuzzy Control. Springer-Verlag Berlin Heidelberg, 1993
  2. J. Lee, 'On methods for improving performance of PI-type fuzzy logic controllers,' IEEE trans. Fuzzy Syst, vol. 1, no. 4, pp. 298-301, 1993 https://doi.org/10.1109/91.251930
  3. K. L. Tang and R. J. Mulholland, 'Comparing fuzzy logic with classical controller design,' IEEE Trans. Syst,, Man, Cybern., vol. 17, no. 6, pp. 1085-1087, 1987 https://doi.org/10.1109/TSMC.1987.6499321
  4. H. X. Li and H. B. Gatland, 'A New Methodology for Designing a Fuzzy Logic Controller,' IEEE Trans. Syst., Man, Cybern., vol. 25, no. 3, pp. 505-512, 1995 https://doi.org/10.1109/21.364863
  5. H. X. Li and H. B. Gatland, 'Conventional Fuzzy Control and Its Enhancement,' IEEE Trans. Syst., Man, Cybem.(B), vol. 26, no. 5, pp. 791-797, 1996 https://doi.org/10.1109/3477.537321
  6. R. Palm, 'Robust Control by Fuzzy Sliding Mode', Automatica, vol. 30, no. 9, pp. 1429-1437, 1994 https://doi.org/10.1016/0005-1098(94)90008-6
  7. W.R. Strugen and MV. Loscutoff, 'Application of Modal Control and Dynamic Observers to Control of a Double Inverted Pendulum,'
  8. K, Furuta and M. Yamakita, 'Swing up Control of Inverted Pendulum,' IECON '91, pp. 2193-2198, 1991
  9. C.-G. Lhee, Design of Fuzzy-Neural Sliding Mode Controller for Implement of tracking Performance, Ph. D. Dissertation, Kook Min University, 1999
  10. B. J. Choi, S. W. Kwak and B. K. Kim, 'Design and Stability Analysis of Single-Input Fuzzy Logic Controller,' IEEE Trans. Syst., Man, Cybem.(B), vol. 30, no. 2, pp. 303-309, 2000 https://doi.org/10.1109/3477.836378
  11. S. Galichet and L. Foulloy, 'Fuzzy controllers : Synthesis and Equivalences,' IEEE Trans. Fuzzy Syst., vol. 3, no. 2, pp. 140-148, 1995 https://doi.org/10.1109/91.388169
  12. H. L. Malki, H. Li, and G. Chen, 'New design and stability analysis of fuzzy PD control systems,' IEEE Trans. Fuzzy Syst., vol. 2, no. 4, pp. 245-254, 1994 https://doi.org/10.1109/91.324804
  13. C. J. Harris, C. G. Moore, and M. Brown, Intelligent Control : Aspects of Fuzzy Logic and Neural Nets. World Scientific, 1993