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Learning-While Controlling RBF-NN for Robot Dynamics Approximation in Neuro-Inspired Control of Switched Nonlinear Systems
Klecker, Sophie; Hichri, Bassem; Plapper, Peter
2018In Artificial Neural Networks and Machine Learning; ICANN 2018 part 3
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Keywords :
RBF-NN; Learning-while controlling; Switching constraints
Abstract :
[en] Radial Basis Function-Neural Networks are well-established function approximators. This paper presents an adaptive Gaussian RBF-NN with an extended learning-while controlling behaviour. The weights, function centres and widths are updated online based on a sliding mode control element. In this way, the need for fixing parameters a priori is overcome and the network is able to adapt to dynamically changing systems. The aim of this work is to present an extended adaptive neuro-controller for trajectory tracking of serial robots with unknown dynamics. The adaptive RBF-NN is used to approximate the unknown robot manipulator dynamics-function. It is combined with a conventional controller and a bio-inpsired extension for the control of a robot in the presence of switching constraints and discontinuous inputs. Its learned goal-directed output results from the complementary action of an actuator, A, and a prventer, P. The trigger is an incentive, I, based on the weighted perception of the enviornment. The concept is validated through simulations and implementation on a KUKA LWR4-robot.
Disciplines :
Computer science
Author, co-author :
Klecker, Sophie ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
Hichri, Bassem ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
Plapper, Peter ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
External co-authors :
no
Language :
English
Title :
Learning-While Controlling RBF-NN for Robot Dynamics Approximation in Neuro-Inspired Control of Switched Nonlinear Systems
Publication date :
2018
Event name :
27th International Conference on Artificial Neural Networks - ICANN 2018
Event organizer :
European Neural Network Society - ENNS
Event place :
Rhodes, Greece
Event date :
from 04-10-2018 to 07-10-2018
Audience :
International
Main work title :
Artificial Neural Networks and Machine Learning; ICANN 2018 part 3
Publisher :
Springer, Cham, Switzerland
ISBN/EAN :
978-3-030-01423-0
Collection name :
Lecture Notes in Computer Science; 11141
Pages :
717-727
Peer reviewed :
Peer reviewed
Available on ORBilu :
since 12 October 2018

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