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Browse Journals & Magazines > Systems, Man, and Cybernetics ...> Volume:32 Issue:1 Help

Fuzzy reinforcement learning control for compliance tasks of robotic manipulators

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2 Author(s)
Tzafestas, S.G. ; Dept. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Greece ; Rigatos, G.G.

A fuzzy reinforcement learning (FRL) scheme which is based on the principles of sliding-mode control and fuzzy logic is proposed. The FRL uses only immediate reward. Sufficient conditions for the convergence of the FRL to the optimal task performance are studied. The validity of the method is tested through simulation examples of a robot which deburrs a metal surface

Published in:
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on  (Volume:32 ,  Issue: 1 )

Date of Publication: Feb 2002

Page(s):
107 - 113
ISSN :
1083-4419
INSPEC Accession Number:
7163852
Digital Object Identifier :
10.1109/3477.979965
Product Type:
Journals & Magazines
Date of Current Version :
07 August 2002
Issue Date :
Feb 2002
Sponsored by :
IEEE Systems, Man, and Cybernetics Society

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