Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
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Control of a Heavy Load Pointing System Using Neural Networks

신경회로망을 이용한 대부하 표적지향 시스템 제어

  • Published : 2004.05.01
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Abstract

This paper presents neural network based controller using the feedback error loaming technique for a heavy load pointing system. Also the mathematical model was developed to analyze heavy load pointing system. The control scheme consists of a feedforward neural network controller and a fixed-gain feedback controller. This neural network controller is trained so as to make the output of the feedback controller zero. The proposed controller is compared with the conventional PI controller through simulations, and the results show that the pointing accuracy of the proposed control system are improved against the disturbance induced by vehicle running on the bump course.

Keywords

References

  1. Lee, D. O., Kang, T. H., Kim, H. S. and Ko, J. H., 'A Feedback Linearization Control Technique Based on Iterative Learning Parameter Identification For an Electrically Driven Stabilized Pointing System of Heavy Turreted Vehicles,' Proceedings of the 10th Mediterranean Conference on Control and Automation, FP7-6, 2002
  2. Kawato, M., Uno, Y., Isobe, M. and Suzuki, R., 'Hierarchical Neural Network Model for Voluntary Movement with Application to Robotics,' 'IEEE Control Systems Magazine, pp. 5-16, April, 1988 https://doi.org/10.1109/37.1867
  3. Lee, B. H., 'Control Performance Evaluation of the Sight Stabilization System in a Gunner's Primary Sight,' Technical Report, Agency for Defence Development, 1997
  4. Eun, S. S., 'Development of the Digital Controller for Electrical Actuation System Using a Brushless DC Motor,' Technical Report, Agency for Defence Development, 1994
  5. Akhyar, S. and Omatu, S., 'Self-Tuning PID Control by Neural Networks,' Proc. of IEEE Int. Joint Conf. on Neural Networks, pp. 2749-2752, 1993 https://doi.org/10.1109/IJCNN.1993.714292
  6. Kim, B. U., Souh, B. Y. and Kim, E. W., 'Unbalance Moment Effect on Gun Stabilization Performance,' Technical Report, Agency for Defence Development, 1995
  7. Sasaki, M., Kawafuku, M. and Takahashi, K., 'Comparison of Feedback Controllers for Feedback-Error-Learning Neural Network Control System with Application to a Flexible Micro-Actuator,' IEEE Int. Conference on System, Man, and Cybernetics, Vol. 5, pp. 4035-4040, Oct. 1997 https://doi.org/10.1109/ICSMC.1997.637294
  8. Almeida Neto, A., Rios Neto, W., Goes, L. C. and Nascimento, Jr., Cairo, L., 'Feedback-Error-Learning for Controlling a Flexible Link,' Proceedings of The 6th Brazilian Symposium on Neural Networks, pp. 273-278, 2000 https://doi.org/10.1109/SBRN.2000.889751
  9. Michael, T. DiRenzo and Mark, W. Vandegrift, 'Adaptive Control for Pointing and Stabilization of a Flexible Gun Tube,' Proceedings of the 36th Conference on Decision and Control, pp. 4943-4948, Dec. 1997 https://doi.org/10.1109/CDC.1997.649827
  10. Lee, D. O., Kim, H. S. and Ahn, T. Y., 'The Research on The GTDS System Design and Development of PI MBT,' Technical Report, Agency for Defence Development, 1995
  11. 최근국, 이만형, 안태영, '구동 링크기구 최적설계 분석 및 불균형 대부하 고저 구동/제어 성능추정 프로그램 개발,' 한국정밀공학회 추계 학술대회 논문집, pp. 614-617, 1997
  12. 제롬 살랑선네, 윤여홍, 장봉춘, 이성철, '차동 제동을 이용한 조향제어 시뮬레이션,' 한국정밀공학회지, 제19권, 제1호, pp.65-74, 2002