Browse > Article
http://dx.doi.org/10.5207/JIEIE.2005.19.6.082

D.C. Motor Speed Control by Learning Gain Regulator  

Park, Wal-Seo (원광대학교 전기전자 및 정보공학부)
Lee, Sung-Su (한국산업인력공단 전북직업전문학교 전기제어과)
Kim, Yong-Wook (한국산업인력공단 전북직업전문학교 전기제어과)
Publication Information
Journal of the Korean Institute of Illuminating and Electrical Installation Engineers / v.19, no.6, 2005 , pp. 82-86 More about this Journal
Abstract
PID controller is widely used as automatic equipment for industry. However when a system has various characters of intermittence or continuance, a new parameter decision for accurate control is a bud task. As a method of solving this problem, in this paper, a teaming gain regulator as PID controller functions is presented. A propriety teaming gain of system is decided by a rule of Delta learning. The function of proposed loaming gain regulator is verified by simulation results of DC motor.
Keywords
learning function; learning gain regulator;
Citations & Related Records
연도 인용수 순위
  • Reference
1 K. J. Astrom, Automatic tuning of PID controller, Sumit Technical Associates Inc. 1988
2 Z. Y. Zhao, M. Tomizuka and S. Tsaka, 'Fuzzy gain scheduling of PID controllers' .IEEE Trans. syst. Vol. 23, No. 5, pp. 1393-1397, September/October, 1993
3 K. J. Astrom, B.Wittenmark, Adaptive control, Addison-Wesley publishing company, 1995
4 N. Hovakimyan, F. Nardi, A. Calise, 'Adaptive Output feedback control of Uncertain'. IEEE Trans. Neural Network, Vol. 13, No. 6, pp. 1420-1431. November 2002   DOI   ScienceOn
5 K. J. Åström, B. Wittenmark 'Adaptive control' 1995 by Addison-wesley publishing company
6 W. Jin, G. Wenzhong, G. Shusheng, 'PID - like controller using a modified neural network', International Journal of System, vol. 28, number 8, pp. 809 - 815, 1997   DOI   ScienceOn
7 K. J. Hunt, D. Sbarbaro, R. Zbikowski, and P. J. Gawthrop, 'Neural Networks for control system-A survey', Automatic, Vol. 28, No. 6, pp. 1083-1112, 1992   DOI   ScienceOn
8 J. Q. Hong, F.L. Lewis, 'Neural-Network Predictive Control for Nonliner dynamic systems with Time-Delay', IEEE Trans. Neural Networks, Vol. 14, No. 2, pp. 377-389, March 2003   DOI   ScienceOn