The Transactions of the Korean Institute of Electrical Engineers D (대한전기학회논문지:시스템및제어부문D)

The Korean Institute of Electrical Engineers (대한전기학회)
권호 표지

Depth Control of Underwater Flight Vehicle Using Fuzzy Sliding Mode Controller and Neural Network Interpolator

퍼지 슬라이딩 모드 제어기 및 신경망 보간기를 이용한 Underwater Flight Vehicle의 심도 제어

  • 김현식 (국방과학연구소) ;
  • 박진현 (진주산업대 산업자동화공학과) ;
  • 최영규 (부산대 전자전기정보컴퓨터공학부)
  • Published : 2001.08.01
Download PDF
⟨ Previous Next ⟩

Abstract

In Underwater Flight Vehicle depth control system, the followings must be required. First, it needs robust performance which can get over modeling error, parameter variation and disturbance. Second, it needs accurate performance which have small overshoot phenomenon and steady state error to avoid colliding with ground surface or obstacles. Third, it needs continuous control input to reduce the acoustic noise and propulsion energy consumption. Finally, it needs interpolation method which can sole the speed dependency problem of controller parameters. To solve these problems, we propose a depth control method using Fuzzy Sliding Mode Controller with feedforward control-plane bias term and Neural Network Interpolator. Simulation results show the proposed method has robust and accurate control performance by the continuous control input and has no speed dependency problem.

Keywords

References

  1. R.K. Lea, R. Allen and S.L. Merry, 'A Comparative study of control techniques for an underwater flight vehicle,' International Journal of Systems Science, vol. 30, pp. 947-964, 1999 https://doi.org/10.1080/002077299291831
  2. E. Eugene Allmendinger, 'Submersible Vehicle System Design,' Published by The Society of Naval Architects and Marine Engineers, pp. 250-254, 1990
  3. S. Y. Yang, Path Tracking and Depth Control for Autonomous Underwater Vehicles based on Sliding Mode Control, Ph.D. Thesis, Pusan National University, 1998
  4. D. I. Lee, D. H. Kwak and J. L. Choi, 'An Intelligent Control System Design for Autonomous Underwater Vehicle,' Journal of Control, Automation and Systems Engineering, vol. 3, no. 3, pp. 227-237, 1997
  5. J. L. Choi and C. S. Hwang, 'Real-time Implementation of a Fuzzy Logic Controller for AutoDepth Control System of a Submersible Vehicle,' Trans. KIEE, vol. 44, no. 8, pp. 1075-1084, 1995
  6. L. A. Zadeh, 'Fuzzy Sets,' Information and Control, vol. 8, pp. 338-358, 1965 https://doi.org/10.1016/S0019-9958(65)90241-X
  7. S. V. Drakunov and V. I. Utkin, 'Sliding mode control in dynamics systems,' INT. J. Control, vol. 55, no. 4, pp. 1029-1037, 1992 https://doi.org/10.1080/00207179208934270
  8. J. S. Glower and J. Munighan, 'Design fuzzy controllers from a variable structure standpoint,' IEEE Trans. Fuzzy Systems, vol. 5, pp. 138-144, 1997 https://doi.org/10.1109/91.554460
  9. M. B. Ghalia, A. T. Alouani, 'Sliding Mode Control Synthesis Using Fuzzy Logic,' Proc. of the American Control Conference, Seattle, Washington, pp. 1528-1532, 1995
  10. Cornelius T. Leondes, FUZZY THEORY SYSTEMS, Academic Press, 1999
  11. Jacek M. Zurada, Introduction to Artificial Neural Systems, West Publishing Company, 1992
  12. Morton Gertler and Grant R. Hagen, Standard Equation of Motion for Submarine Simulation, TASK, June 1967
  13. H.C. Lee et al, Computer Graphics and Geometric Modeling for Engineers, Sigma Press, pp. 261-266, 1996
  14. Howard Demuth and Mark Beale, Neural Network Toolbox User's Guide, The MathWorks Inc., pp. 5-20, 1994