Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
권호 표지

Design of a sliding Mode Controller Using a Neural Compensator

신경회로망 보상기를 이용하는 슬라이딩 모드 제어기 설계

  • 이민호 (경북대학교 센서기술연구소/센서공학과) ;
  • 정순기 (경북대학교 컴퓨터공학과)
  • Published : 2000.03.01
Download PDF
⟨ Previous Next ⟩

Abstract

This paper proposes a new sliding mode controller combined with a multi-layer neural network using the error back propagation learning algorithm,, The network acts as a compensator of the conventional sliding mode controller to improve the control performance when initial assumptions of uncertainty bounds of system parameters are violated. The proposed controller can reduce th steady state error of conventional sliding mode controller with the boundary layer technique Computer simulation results show that the proposed method is effective to control dynamic systems with unexpectably large uncertainties.

Keywords

References

  1. U. Itkis, Control Systems of variable structure, John Wiely & Sons, INC, New York, 1976
  2. V I. Utkin, 'Variable structure systems with sliding mode,' IEEE Trans. on Automatic Control, vol. AC-22, no. 2, pp. 212-222, 1977
  3. J H. Lee, J. S Ko, S. K. Chung, D. S. Lee, and M J. Youn, 'Continuous variable structure controller for BLDDSM position control with prescribed tracking performance.' IEEE trans. on Industrial Electronics, vol. 41, no. 2, pp. 483-491, 1994 https://doi.org/10.1109/41.315266
  4. M. W. Spong, 'On the robust control of robot manipulators,' IEEE Trans. on Automatic Control, vol. 37, no. 11, pp. 1782-1786, 1992 https://doi.org/10.1109/9.173151
  5. R. Gorez, 'Conclusions of 5-year-investigations in sliding mode control of robot manipulators,' Europeans Control Conf., F1029-5, pp. 102, 1999
  6. J. Y. Hung, W. Gao, and J. C Hung, 'Variable Structure cont'
  7. B Curk and K. Jezernik, 'Perturbation estimation in sliding modrol : A surver,' IEEE Trans. on Industrial Electronics, vol. 40, no. 1, pp. 2-22, 1993. 'e motion control,' European Control Conf., F510, pp. 191, 1999 https://doi.org/10.1109/41.184817
  8. J. J. Slotine, 'Sliding controller design for nonlinear systems,' International Journal of Control, vol. 40, no. 2, pp. 421-434, 1984 https://doi.org/10.1080/00207178408933284
  9. F. J. Chang and S. H. Twu, 'Adaptive chattering alleviation of variable structure systems control,' IEE Proc. Part D, vol. 137, no. 1, 1990
  10. D. S. Yoo and M. J. Chung, 'A variable structure control with simple adaptation laws for upper bounds on the norm of the uncertainties,' IEEE Trans. on Automatic Control, vol. 37, no. 6, pp. 860-864, 1992 https://doi.org/10.1109/9.256348
  11. D. Rumelhart, G. E. Hilton, and R J. Williams , 'Learning internal representation by error propagation,' Parallel Distributed Processing, D. Rumelhart and J McCleland(Eds.), vol. 1, MIT Press, 1986
  12. M. Lee, S. Y. Lee, and C. H. Park, 'Neural controller of nonlinear dynamic systems using higher order neural networks,' Electronics Letters, vol. 28, no. 3, pp. 276-277, 1992 https://doi.org/10.1049/el:19920170
  13. M. Kawato, 'Feedback-error-learning neural network for trajectory control of a robotic manipulator,' Neural Networks, vol. 1, pp. 251-265, 1988 https://doi.org/10.1016/0893-6080(88)90030-5
  14. T. L. Chern and Y. C. Wu, 'An optimal variable structure control with integrated compensation for electrohydraulic position servo control system,' IEEE Trans. on Industrial Electronics, vol. 39, no. 5, pp. 460-464, 1992 https://doi.org/10.1109/41.161478