Brief Robust neural control for robotic manipulators

Authors:
Oscar Barambones;Victor Etxebarria
Affiliations:
Dpto. Ingenierıa de Sistemas y Automática E.U.I.T.I Bilbao. Universidad del Paıs Vasco. P. La Casilla, 48012 Bilbao, Spain;Dpto. de Electricidad y Electrónica. Facultad de Ciencias. Universidad del Paıs Vasco. Apdo. 644. 48080 Bilbao, Spain
Venue:
Automatica (Journal of IFAC)
Year:
2002

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Abstract

A robust neural control scheme for mechanical manipulators is presented. The design basically consists of an adaptive neural controller which implements a feedback linearization control law for a generic manipulator with unknown parameters, and a sliding-mode control which robustifies the design and compensates for the neural approximation errors. It is proved that the resulting closed-loop system is stable and that the trajectory-tracking control objective is achieved. Some simulation results are also provided to evaluate the design.