Robust adaptive friction compensation in servo-drives using position measurement only

Proceedings of the 2000. IEEE International Conference on Control Applications. Conference Proceedings (Cat. No.00CH37162) ◽

10.1109/cca.2000.897420 ◽

2002 ◽

Cited By ~ 2

Author(s):

Zhi Wang ◽

H. Melkote ◽

F. Khorrami

Keyword(s):

Friction Compensation ◽

Position Measurement ◽

Servo Drives ◽

Robust Adaptive

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Robust adaptive friction compensation for tracking control of robots

Proceedings of the 1999 IEEE International Conference on Control Applications (Cat. No.99CH36328) ◽

10.1109/cca.1999.807854 ◽

2003 ◽

Author(s):

P. Tomei

Keyword(s):

Tracking Control ◽

Friction Compensation ◽

Robust Adaptive

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Robust adaptive deadzone and friction compensation of robot manipulator using RWCMAC network

Journal of Mechanical Science and Technology ◽

10.1007/s12206-011-0328-9 ◽

2011 ◽

Vol 25 (6) ◽

pp. 1583-1594 ◽

Cited By ~ 7

Author(s):

Seong Ik Han ◽

Kwon Soon Lee ◽

Min Gyu Park ◽

Jang Myung Lee

Keyword(s):

Robot Manipulator ◽

Friction Compensation ◽

Robust Adaptive

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High-accuracy robust adaptive motion control of a torque-controlled motor servo system with friction compensation based on neural network

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1177/0954406218783017 ◽

2018 ◽

Vol 233 (7) ◽

pp. 2318-2328 ◽

Cited By ~ 2

Author(s):

Jian Hu ◽

Yuangang Wang ◽

Lei Liu ◽

Zhiwei Xie

Keyword(s):

Neural Network ◽

Motion Control ◽

Servo System ◽

High Accuracy ◽

Robust Adaptive Control ◽

Lyapunov Theory ◽

Parametric Estimation ◽

Friction Compensation ◽

Nonlinear Friction ◽

Robust Adaptive

In this paper, a high-accuracy motion control of a torque-controlled motor servo system with nonlinear friction compensation is presented. Friction always exists in the servo system and reduces its tracking accuracy. Thus, it is necessary to compensate for the friction effect. In this paper, a novel controller that combines robust adaptive control with friction compensation based on neural network observer is proposed. An improved LuGre friction model is applied into the friction compensation as it is known as a good model to express the nonlinear friction. A single hidden-layer network is utilized to observe the immeasurable friction state. Then, the robust adaptive controller is used to handle the parametric uncertainty, the parametric estimation error, friction compensation error, and other uncertainties. Lyapunov theory is utilized to analyze the stability of the closed-loop system. The experimental results demonstrate the effectiveness of the proposed algorithm.

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