Browse > Article

LuGre Model-Based Neural Network Friction Compensator in a Linear Motor Stage  

Horng, Rong-Hwang (Department of Mechanical Engineering, Graduate school, National Chiao-Tung University)
Lin, Li-Ren (Department of Mechanical Engineering, Graduate school, National Chiao-Tung University)
Lee, An-Chen (Department of Mechanical Engineering, National Chiao-Tung University)
Publication Information
International Journal of Precision Engineering and Manufacturing / v.7, no.2, 2006 , pp. 18-24 More about this Journal
Abstract
This paper proposes a LuGre Model-Based Neural Network (MBNN) friction compensation algorithm for a linear motor stage. For matching the friction phenomena in both the motion-start region and the motion-reverse region, the LuGre dynamic model is employed into the proposed compensation algorithm. After training of the model-based neural network is completed, the estimated friction for compensation is obtained. From the obtained result we find that the new structure gains advantage over the non-friction compensation system on the performance of the compensator in both regions. The proposed compensator is evaluated and compared experimentally with an uncompensated system on a microcomputer controlled linear motor tracking system in the final section of the paper. The experimental results show the improvement on the maximum velocity error and the root mean square tracking error in the motion-start region ranges from 34% to 53% and from 53% to 75% respectively, and in the motion-reverse region from 48% to 65% and from 79% to 90% respectively.
Keywords
Linear-Motor-Driven Motion System; LuGre Friction Model; LuGre Model-Based Neural Network; Friction compensation;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Armstrong, Helouvry B., Dupont, P. and Canudas, de Wit C., 'A survey of models, analysis tools and compensation methods for the control of machines with friction,' Automatica, Vol. 30, No. 7, pp.1083–1138, 1994
2 Canudas, de Wit C., Olsson, H., Astrom, K. J. and Lischinsky, P., 'A new model for control of systems with friction,' IEEE Trans. on Automatic Control, Vol. 40, No. 3, pp. 419-425, 1995   DOI   ScienceOn
3 Gao, X. Z. and Ovaska, S. J., 'Friction compensation in servo motor systems using neural networks,' Proc. Of the 1999 IEEE Midnight sun Workshop on Soft computing Methods in Industrial Applications, Kuusama, Finland, pp.146-151, June 1999
4 Gan, Chengyu and Danai, Kourosh, 'Model-based recurrent neural network for modeling nonlinear dynamic system,' IEEE Transactions on Systems, Man and cybernetics-part b:cybernetics, Vol. 30, No. 2, pp. 344-351, April 2000   DOI   ScienceOn
5 Edward, P.C., 'Digital filtering,' Houghton Mifflin Co., Chap. 9, 1992
6 'PLATINUM DDL and SERVOSTAR setup Guide,' Document number: M-LN-016-0702, Kollmorgen, a Danaher Motion Company, June 2002
7 Dahl, P., 'Solid friction damping of mechanical vibrations,' AIAA Journal, Vol. 14, No. 12, pp. 1675-1682, 1976   DOI   ScienceOn
8 Berger, E. J., 'Friction modeling for dynamic system simulation,' ASME J. of Applied Mechanics Reviews, Vol. 55, No. 6, pp. 535-577, 2002   DOI   ScienceOn
9 Sepehri, N., Sassini, F., Lawrence, P. D. and Ghasempoor, A., 'Simulation and experimental studies of gear backlash and stickslip friction in hydraulic excavator swing motion,' ASME J. of Dynamic Systems, Measurement and Control, Vol. 118, pp. 463-467,1996   DOI   ScienceOn
10 Kovacic, Z., Petik, V. and Bogdan, S., 'Neural network-based friction and nonlinear load compensator,' Proc. of the 1999 IEEE International Symposium on Industrial Electronics, Vol. 1, pp. 157 – 162, July 1999
11 Werbos, Paul J., 'Backpropagation Through Time: What it dose and How to do it,' Proc. Of the IEEE, Vol. 78, No. 10, pp. 1550-1560, October 1990   DOI   ScienceOn
12 Shih, Y.T., 'The High Precision Control for a Linear-Motor- Driven Motion Stage with Friction Compensation,' Doctor Thesis, National Chiao-Tung University, Hsinchu City, Taiwan, 2004
13 Leine, R. I., Campen, van D. H., Kraker, de A. and Steen,van den L., 'Stick-slip vibrations induced by alternate friction models,' Nonlinear Dynamics, Vol.16, pp. 41-54, 1998   DOI
14 Armstrong, Helouvry B., 'Control of machines with friction,' Kluwer Academic Publishers, Nowell, MA, 1991
15 Karnopp, D., 'Computer simulation of stick-slip friction in mechanical dynamic systems,' ASME J. of Dynamic systems, Measurement and Control, Vol. 107, No. 1, pp. 100-103, 1985   DOI
16 Yen, Chen Wen V., Liu, Tsong Zen and Wang, Tsang Yi, 'A neural-network-based velocity tracking control method for direction-changing motions,' Control Engineering Practices, Vol.5, No.8, pp. 1071-1076, 1997   DOI   ScienceOn