Tuning convergence rate of a robust learning controller for robot manipulators

This paper presents a robust learning control algorithm which learns the entire span of robot trajectory within a finite time interval. The learning controller treats the uncertain parameters as well as unknown external disturbances with the aid of the linear parameterization property of the robot system and robust feedback control input. It is shown that the robot motion converges exponentially to the desired one as the iteration continues.

[1]  Masayoshi Tomizuka,et al.  A unified approach to the design of adaptive and repetitive controllers for robotic manipulators , 1990 .

[2]  Tae-Yong Kuc,et al.  An iterative learning control of robot manipulators , 1991, IEEE Trans. Robotics Autom..

[3]  Suguru Arimoto,et al.  Bettering operation of Robots by learning , 1984, J. Field Robotics.

[4]  Christopher G. Atkeson,et al.  Robot trajectory learning through practice , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[5]  J. S. Lee,et al.  An adaptive learning control of uncertain robotic systems , 1991, [1991] Proceedings of the 30th IEEE Conference on Decision and Control.

[6]  Luca Maria Gambardella,et al.  On the iterative learning control theory for robotic manipulators , 1988, IEEE J. Robotics Autom..

[7]  Shinji Hara,et al.  Stability of repetitive control systems , 1985, 1985 24th IEEE Conference on Decision and Control.

[8]  Weiping Li,et al.  Composite adaptive control of robot manipulators , 1989, Autom..

[9]  Roberto Horowitz,et al.  A new adaptive learning rule , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[10]  Filson H. Glanz,et al.  Application of a General Learning Algorithm to the Control of Robotic Manipulators , 1987 .