Implementating a hybrid learning force control scheme

Author

Guglielmo, Kennon ; Sadegh, Nader

Author_Institution

Southwest Res. Inst., San Antonio, TX, USA

Volume

14

Issue

1

fYear

1994

Firstpage

72

Lastpage

79

Abstract

The theory and implementation of a repetitive learning control algorithm for hybrid position and force control of robotic manipulators is presented here. The complete control system involves 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 is used to evaluate the performance of the proposed controller.<>

Keywords

adaptive control; feedback; force control; learning (artificial intelligence); learning systems; manipulators; position control; IBM 7545 robot; hybrid position and force control; learning force control scheme; learning orientation control; learning position control; repetitive learning control algorithm; robotic manipulators; torque feedback; translational motion; unknown surface; 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

Journal_Title

Control Systems, IEEE

Publisher

ieee

ISSN

1066-033X

Type

jour

DOI

10.1109/37.257897

Filename

257897