Title :
A learning algorithm for hybrid force control of robot arms
Author :
Lucibello, Pasquale
Author_Institution :
Dipartmento di Inf. e Sistemistica, Roma Univ., Italy
Abstract :
An investigation of the hybrid force control of robot arms by learning is presented. A force control scheme based on feedback linearization is used to build an algorithm that improves, trial by trial, force and position tracking over a finite time interval. Unlike other published learning control schemes, the proposed algorithm does not rely on high-gain feedback. Robustness and convergence in spite of sufficiently small system parameter uncertainties and disturbances is proved by means of the contraction mapping principle
Keywords :
adaptive control; feedback; force control; learning (artificial intelligence); linearisation techniques; manipulators; position control; tracking; contraction mapping principle; convergence; feedback linearization; hybrid force control; learning algorithm; manipulators; position tracking; robot arms; robustness; Convergence; Error correction; Force control; Force feedback; H infinity control; Manipulators; Orbital robotics; Robots; Robust control; Trajectory;
Conference_Titel :
Robotics and Automation, 1993. Proceedings., 1993 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-8186-3450-2
DOI :
10.1109/ROBOT.1993.292053
