Learning hybrid force and position control of robot manipulators

The learning control is applied to hybrid force and position control of robot manipulators. When the geometry and position of a constraint surface is known, the hybrid force and position controller and the feedforward compensator can be designed in the constraint coordinates. When the operation is periodic, the learning hybrid force and position control enhance the control performance as the feedforward compensator is updated in each cycle by the force and position error in the preceding trials. This scheme is proved to be asymptotically stable. A two degree of freedom SCARA-type direct-drive robot manipulator is used to test the learning hybrid force and position control. The deburring tool mounted on the upper link of the robot could follow a flat, tilted flat, and curved 1/4 " aluminum plate with a desired contact force of 10 N (within the root-mean-square force error of 1.95 N) and with a desired tangential velocity. The experiments confirmed the effectiveness of the learning hybrid force and position controller. >

[1]  Roberto Horowitz,et al.  Learning Control of Robot Manipulators , 1993 .

[2]  John J. Craig,et al.  Hybrid position/force control of manipulators , 1981 .

[3]  Tsuneo Yoshikawa,et al.  Dynamic hybrid position/force control of robot manipulators--Description of hand constraints and calculation of joint driving force , 1986, IEEE Journal on Robotics and Automation.

[4]  Roberto Horowitz,et al.  A new adaptive learning rule , 1991 .

[5]  Roberto Horowitz,et al.  Stability and Robustness Analysis of a Class of Adaptive Controllers for Robotic Manipulators , 1990, Int. J. Robotics Res..

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

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

[8]  Weiping Li,et al.  Adaptive strategies in constrained manipulation , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

[9]  Masayoshi Tomizuka,et al.  Discrete time repetitive control for robot manipulators , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[10]  J. Marsden,et al.  Elementary classical analysis , 1974 .

[11]  Roberto Horowitz,et al.  Digital implementation of repetitive controllers for robotic manipulators , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[12]  Daniel E. Whitney,et al.  Development and Control of an Automated Robotic Weld Bead Grinding System , 1990 .

[13]  Kozo Ono,et al.  Force controlled robot for grinding , 1990, EEE International Workshop on Intelligent Robots and Systems, Towards a New Frontier of Applications.

[14]  S. Hara,et al.  Repetitive control system: a new type servo system for periodic exogenous signals , 1988 .

[15]  Oussama Khatib,et al.  A unified approach for motion and force control of robot manipulators: The operational space formulation , 1987, IEEE J. Robotics Autom..

[16]  M. Tomizuka,et al.  Digital control of repetitive errors in disk drive systems , 1990, IEEE Control Systems Magazine.

[17]  F. Miyazaki,et al.  Applications of learning method for dynamic control of robot manipulators , 1985, 1985 24th IEEE Conference on Decision and Control.