COMPARISON OF TECHNIQUES FOR PREDICTION OF FUTURE POSITIONS IN TRAJECTORY TRACKING OF AN OBJECT BY DC DRIVES

Authors

  • Qazi S.M. Zia-ul-Haque KINPOE, Karachi Nuclear Power Complex, Paradise Point, Karachi, Pakistan
  • N. R. Jadoon KINPOE, Karachi Nuclear Power Complex, Paradise Point, Karachi, Pakistan

Abstract

Trajectory tracking means to follow the path or trajectory of a moving object. Trajectory tracking finds application in various fields of war and peace. The location of the object can be represented by its rectangular as well as spherical coordinates. The system performing the task was a prototype model of an anti aircraft gun. To point the target by the gun we needed to track only the two spherical coordinates of its position i.e. the angle of azimuth and the vertical angle. To be in coherence with the object, the knowledge of future position was required in advance. However it was not possible to have this knowledge. Good estimates of the future positions could be made from the knowledge of motion so far of the object, thus a good estimation technique was required. The estimation techniques used here included conventional numerical techniques and modern adaptive filtering techniques as well. The paper is based only upon the results of estimation techniques applied. For discussion, only the results for the angle of azimuth are used in the paper. Conventional numerical techniques were found suitable when the object to be tracked moves with smaller degree of non-linearity in its motion and at the transients in terms of error magnitude but are poorer in terms of computing time and steady state error reduction. The adaptive filtering techniques on the other hand are poorer in transient error magnitude but are good in terms of computing time and steady state error reduction.

References

R.L. Burden, J.D. Faires and A.C. Reynolds, “Numerical Analysisâ€, 1st Edition. Wadsworth, Inc (1979).

C. F. Gerald and P. O. Wheatley, “Applied Numerical Analysisâ€, 5th Edition Addison-Wesley Publishing Company (1994).

M. Moonen, “Introduction to Adaptive Signal Processing†Department of Electrical Engineering · ESAT/SISTA K.U. Leuven, Belgium url: www.esat.kueleuven.ac.bc/~ moonen/asp_course.html

O. Macchi and N. J. Bershad, “Adaptive recovery of a chirped sinusoid in noise, 1. Performance of the RLS algorithm,†IEEE Trans. Acoust., Speech, Signal Processing, Vol. 39 (Mar. 1991), pp. 583–594,.

P. C. Wei, J. R. Zeidler, and W. H. Ku, “Adaptive recovery of a chirped signal using the RLS algorithm,†IEEE Trans. Signal Processing, vol. 45 (Feb. 1997) p. 969–976,.

National Power ICs. “LM628/LM629 Precision Motion Controller. National Semiconductors (1995).

Downloads

Published

09-07-2020

How to Cite

[1]
Q. S. Zia-ul-Haque and N. R. Jadoon, “COMPARISON OF TECHNIQUES FOR PREDICTION OF FUTURE POSITIONS IN TRAJECTORY TRACKING OF AN OBJECT BY DC DRIVES”, The Nucleus, vol. 41, no. 1-4, pp. 7–17, Jul. 2020.

Issue

Section

Articles