摘要
Precision positioning systems driven by linear motors are vulnerable to force disturbances owing to the reduction of gear transmission. The friction, included in the disturbance, can be modeled and compensated to improve the servo performance. This paper proposes a modified Stribeck friction model （SFM） and an optimization algorithm for consistency with the positioning platform. The compensators based on the friction model and disturbance observer （DOB） are simulated. The simulation results show that as compared with the DOB compensator （the velocity recovers by 5.19%）, the friction model based compensator （the velocity recovers by 10.66%） exhibits a better performance after adding the disturbance. Moreover, compensation comparisons among the Coulomb friction, traditional SFM, and modified SFM are performed. The experimental results show that the following error with modified SFM compensation improves by 67.67% and 51.63% at a speed of 0.005 m/s and 0.05 m/s, compared with the Coulomb friction compensation. This demonstrates that the proposed model, optimization algorithm, and compensator can reduce the following error effectively.
Precision positioning systems driven by linear motors are vulnerable to force disturbances owing to the reduction of gear transmission. The friction, included in the disturbance, can be modeled and compensated to improve the servo performance. This paper proposes a modified Stribeck friction model （SFM） and an optimization algorithm for consistency with the positioning platform. The compensators based on the friction model and disturbance observer （DOB） are simulated. The simulation results show that as compared with the DOB compensator （the velocity recovers by 5.19%）, the friction model based compensator （the velocity recovers by 10.66%） exhibits a better performance after adding the disturbance. Moreover, compensation comparisons among the Coulomb friction, traditional SFM, and modified SFM are performed. The experimental results show that the following error with modified SFM compensation improves by 67.67% and 51.63% at a speed of 0.005 m/s and 0.05 m/s, compared with the Coulomb friction compensation. This demonstrates that the proposed model, optimization algorithm, and compensator can reduce the following error effectively.
基金
Funding was provided by Shanghai Municipal Natural Science Foundation （Grant No. 13ZR1415800）, National Natural Science Foundation of China （Grant No. 61573238）, Innovation Program of Shanghai Municipal Education Commission of China （Grant No. 14YZ008）, Jiangsu Key Laboratory for Advanced Robotics Technology Foundation （Grant No. JAR201304）.
