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LuGre Model-Based Neural Network Fiction Compensator in a Linear Motor Stage
Rong-Hwang Horng,Li Ren Lin,An-Chen Lee 한국정밀공학회 2006 International Journal of Precision Engineering and Vol.7 No.2
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 hat 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.
LuGre Model-Based Neural Network Friction Compensator in a Linear Motor Stage
Horng, Rong-Hwang,Lin, Li-Ren,Lee, An-Chen Korean Society for Precision Engineering 2006 International Journal of Precision Engineering and Vol.7 No.2
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.
Advanced Parameter Identification for a Linear-Motor-Driven Motion System Using Disturbance Observer
Yi-Ren Pan,An-Chen Lee,Yi-Ti Shih,Rong-Hwang Horng 한국정밀공학회 2009 International Journal of Precision Engineering and Vol. No.
Disturbance observer (DOB) is generally introduced into motion control systems to eliminate undesired disturbances and plant uncertainty. The DOB is also used for system identification. This work presents a novel experimental identification algorithm using disturbance observer to identify inertia, viscous coefficient, and friction of linear-motor-driven motion system. A conventionally adopted algorithm for determining the inertia of the motion system based on orthogonal relations among system responses is modified and extended to estimate the viscous coefficient and the magnitude of Coulomb friction of the underlying system. The advantages of the proposed method are high convergence rate and only one experiment needed to evaluate the system parameters. The proposed algorithm is demonstrated to be workable by both simulation and experiment.