DOI QR코드

DOI QR Code

Adaptive Disturbance Compensation Control for Heavy Load Target Aiming Systems to Improve Stabilization Performances

대부하 표적 지향시스템의 안정화 성능향상을 위한 외란보상 적응제어

  • Published : 2005.11.01

Abstract

Stabilization error of target aiming systems mounted on moving vehicles is an important performance because the error directly affects hit Probability. In a heavy load targetaiming system, the disturbance torque comes from mass unbalance and linear acceleration is a main source of stabilization error. This study suggests an experimental design method of disturbance feedforward compensation control to improve the stabilization performance of heavy load target aiming systems. The filtered_x least square(FxLMS) algorithm is used to estimate the compensator coefficients adaptively. The proposed control is applied to a simple experimental set-up which simulates dynamic characteristics of a real target aiming system. The feasibility of the proposedtechnique is illustrated, along with results of experiments.

Keywords

References

  1. Kim, B. U. and Kang, E. S., 2004, 'Control of a Heavy Load Pointing System Using Neural Networks,' J. of KSPE, Vol. 21, No. 5, pp. 55-63
  2. Kang, M. S., Lyu, J., Seok, H. D, and Lim, J. K, 2004, Analysis of Stabilization Error Sources for Main Battle Tank, Proceedings of Seminar for Ground Weapon Systems Development, pp. 12-15
  3. White, M. T. and Tomizuka, M., 1997, 'Increased Disturbance Rejection in Magnetic Disk Drives by Acceleration Feedforward Control and Parameter Adaptation', Control Engineering Practice, Vol. 5, No. 6, pp. 741-751 https://doi.org/10.1016/S0967-0661(97)00058-0
  4. Suzuki, Y., 1998, 'Acceleration Feedforward Control for Active Magnetic Bearing Excited by Ground Motion', IEEE Proc. Control Theory Appl., Vol. 145, No. 2, pp. 113-118 https://doi.org/10.1049/ip-cta:19981751
  5. Widrow, B., Glover, J. R., McCool, J. M., Kaunitz, J., Williams, C. S., Hern, R. H., Zeidler, J. R., Dong, E. and Goodlin, R. C., 1975, 'Active Noise Canceling: Principles and Applications,' Proc. IEEE, Vol. 63, pp. 1692-1716 https://doi.org/10.1109/PROC.1975.10036
  6. Kuo, S. M. and Morgan, D. R., 1996, Active Noise Control Systems, A Wiley-Interscience Publication, John Wiley & Sons, Inc
  7. Widrow, B. and Stearns, S. D., 1985, Adaptive Signal Processing, Prentice-Hall, Englewood Cliffs, NJ
  8. Reason, J. and Ren, W., 1993, 'Estimating the Optimal Adaptive Gain for the LMS Algorithm,' Proceedings of CDC, San Antonio, pp. 1587-1588
  9. Lee, K. S., 2003, 'Convergence of the Filtered-x Least Mean Square Adaptive Algorithm for Active Noise Control of a Multiple Sinusoids,' Transactions of the KSNVE, Vol. 13, No. 4, pp. 239-246
  10. Kang, M. S., 2003, 'Acceleration Feedforward Control in Active Magnetic Bearing System Subject to Base Motion by Filtered-x LMS Algorithm', Transactions of the KSME(A), Vol. Vol. 27, No. 10, pp. 1722-1719
  11. Kang, M. S. and Jung, J. S., 2004, 'Disturbance Compensation Control of An Active Magnetic Bearing System by Multiple FxLMS Algorithm-theory', J. of KSPE, Vol. 21, No. 2, pp. 74-82
  12. Kang, M. S., 2005, 'Geometric Analysis of Convergence of FxLMS Algorithm,' Transactions of the KIEE, Vol. 54D, No. 1, pp. 40-47
  13. Ljung, L., 1977, 'Analysis of Recursive Stochastic Algorithm,' IEEE Transactions on Automatic Control, Vol. AC-22, No. 4, pp. 551-575

Cited by

  1. Real-time Unbalance Moment Compensation Method for Line of Sight(LOS) Stabilization Control System vol.26, pp.3, 2016, https://doi.org/10.5050/KSNVE.2016.26.3.323