Design of a Neuro-Fuzzy Observer for Speed-Sensorless Control of DC Servo Motor

직류 서보 전동기 센서리스 속도제어를 위한 뉴로-퍼지 관측기 설계

  • 안창환 (인하공업전문대학 디지털전자정보과)
  • Published : 2007.09.01

Abstract

This paper deals with speed-sensorless control of DC servo motor using Neuro-Fuzzy Observer. DC servo motor has very low rotor inertia and excellent response characteristic and it is very useful to control torque and speed. It is easy to detect the voltage and current and resolver or encoder is used to measure a rotor speed. But it has a limit as a driving speed to detect speed precisely. So it is problem to improve the performance of the driving system. To solve this problem, it is studied to detect a speed of DC servo motor without sensor. In particular, study on the method to estimate the speed using the observer is performed a lot. In this paper, the gain of the observer is properly set up using the Neuro-Fuzzy control and Neuro-Fuzzy Observer that have a superior transient characteristic and is easy to implement compared the existing method is designed. It calculates the differentiation of the rotor current directly using the rotor current measured in the DC servo motor and estimates the speed of the rotor using the differentiation. Proposed speed sensorless control method is performed using the estimated speed. Also, it is proved feasibility of the proposed observer from the comparison tested a case with a speed sensor and a case without a speed sensor which used a highly efficient drive and 200[w] DC servo motor starting system.

Keywords

References

  1. Masahiro Takigawa, et. al. 'A Wide Speed Control System for Brushless DC Motor Regarding to the Transient Response Characteristics,' T. IEEE Japan, vol.113-D, No.2 pp.151-158, 1993
  2. K, Nandam. Pradeep, 'Analog and Digital Speed Control of DC Drives Using Proportional-Integral and Integral-Proportional control techniques,' IEEE Trans. Ind. Elect., Vol. IE-34, No.2, pp. 227-233, 1987 https://doi.org/10.1109/TIE.1987.350958
  3. H. Nakano and I. Takahashi,'Speed Sensorless Field-Orientation Control of the Induction Motor Using an Instaneous slip Frequency Estimation Method,' IEEE PESC., pp. 847-854, 1988
  4. Joachim Holtz, 'Speed Estimation and Sensorless Control of AC Drives,' IEEE IECON, pp.649-654, 1993
  5. S. K. chang, W. T. You, and D. L. Hsu, 'Design of General Structured Observers for Linear System with Unknown Input,' J. Franklin Inst., Vol.334B, No.2, pp. 213-232. 1997
  6. T.H. Liu and C.P. Cheng, 'Adaptive Control for a Sensorless Permanent-Magnet Synchronous Motor Drive,' IEEE-IECON Conf. Rec., pp.413-418, 1992
  7. G. B. Wang, S. S. Peng, and H. P. Huang, 'A sliling Observer for nonlinear Process Contro,l' Chemical Engineering Science, Vol. 52, pp.787-805, 1997 https://doi.org/10.1016/S0009-2509(96)00449-6
  8. H.K.khalil, 'Numerical Differentiation Using High-Gain Observer,' Proceedings of the 36th IEEE Conference on a decision and Control, Vol. 2, pp. 4790-4795, December 1997
  9. Junhong Nie, 'A Neural Approach to Fuzzy Modeling,' Proceeding of the American Control Conference, pp. 2139-2142, 1994
  10. 이광형, 오길록 공저, '퍼지이론 및 응용', 홍릉과학출판사, pp 5.3-5.6, 1992
  11. G. Griva, F. Profumo, L. Rosell, R. Bojoi, 'Optimization of Fuzzy-Like Luenberger Observer for High Speed Sensorless Induction Motor Drives Using Genetic Algorithms,' IEEE Industry Applications Conference., REc, Vol. 2, pp.1268-1274, Oct 2000
  12. E. Purwanto, Member, IEEE, S. Arifin, Bian-Sioe So, 'Application of Adaptive Neuro Fuzzy Inference System on the Development of the Observer for Speed Sensorless Induction Motor,' IEEE Catalogue No. 01, CH37239, pp. 409-414, 2001