DocumentCode :
1865511
Title :
Theory and implementation of a hybrid learning force control scheme
Author :
Guglielmo, Kennon ; Sadegh, Nader
Author_Institution :
George W. Woodruff Sch. of Mech. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fYear :
1993
fDate :
2-6 May 1993
Firstpage :
659
Abstract :
Theory and implementation of a repetitive learning control algorithm for hybrid position and force control of a robotic manipulator are presented. The complete control system will involve learning position control for translational motion tangent to an unknown surface, learning force control normal to the surface, and learning orientation control using torque feedback to maintain tangential motion relative to the surface. An IBM 7545 robot equipped with a wrist force/torque sensor was used to evaluate the performance of the proposed controller. It was found that the repetitive learning algorithm outperformed a compatible proportional-integral-derivative (PID) controller by a significant margin in terms of the tracking accuracy. This implementation also demonstrates the great flexibility and wide range of application of this control scheme, as well as its robustness to nonperiodic disturbances
Keywords :
adaptive control; feedback; force control; learning (artificial intelligence); manipulators; position control; IBM 7545 robot; hybrid learning force control scheme; nonperiodic disturbances; orientation control; position control; repetitive learning control algorithm; robotic manipulator; robustness; torque feedback; translational motion tangent; wrist force/torque sensor; Control systems; Force control; Force feedback; Force sensors; Manipulators; Motion control; Position control; Robot sensing systems; Torque control; Wrist;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 1993. Proceedings., 1993 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-8186-3450-2
Type :
conf
DOI :
10.1109/ROBOT.1993.292054
Filename :
292054
Link To Document :
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