DECENTRALIZED NEURAL BACKSTEPPING CONTROL FOR AN INDUSTRIAL PA10-7CE ROBOT ARM

R. Garcia Hernandez, E. N. Sanchez, M. A. Llama, J. A. Ruz-Hernandez

Abstract

This paper presents a discrete-time decentralized control strategy for trajectory tracking of a seven degrees of freedom (DOF) robot arm. A high order neural network (HONN) is used to approximate a decentralized control law designed by the backstepping technique as applied to a block strict feedback form (BSFF). The neural network learning is performed online by extended Kalman filter. The local controller for each joint use only local angular position and velocity measurements. The feasibility of the proposed scheme is illustrated via simulation.

References

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Paper Citation


in Harvard Style

Garcia Hernandez R., N. Sanchez E., A. Llama M. and A. Ruz-Hernandez J. (2011). DECENTRALIZED NEURAL BACKSTEPPING CONTROL FOR AN INDUSTRIAL PA10-7CE ROBOT ARM . In Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011) ISBN 978-989-8425-84-3, pages 82-89. DOI: 10.5220/0003684300820089


in Bibtex Style

@conference{ncta11,
author={R. Garcia Hernandez and E. N. Sanchez and M. A. Llama and J. A. Ruz-Hernandez},
title={DECENTRALIZED NEURAL BACKSTEPPING CONTROL FOR AN INDUSTRIAL PA10-7CE ROBOT ARM},
booktitle={Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011)},
year={2011},
pages={82-89},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003684300820089},
isbn={978-989-8425-84-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011)
TI - DECENTRALIZED NEURAL BACKSTEPPING CONTROL FOR AN INDUSTRIAL PA10-7CE ROBOT ARM
SN - 978-989-8425-84-3
AU - Garcia Hernandez R.
AU - N. Sanchez E.
AU - A. Llama M.
AU - A. Ruz-Hernandez J.
PY - 2011
SP - 82
EP - 89
DO - 10.5220/0003684300820089