A HIERARCHICAL FUZZY-NEURAL MULTI-MODEL - An application for a mechanical system with friccion identification and control

Ieroham Baruch, Jose Luis Olivares, Federico Thomas

Abstract

A Recurrent Trainable Neural Network (RTNN) with a two layer canonical architecture and a dynamic Backpropagation learning method are applied for identification and control of complex nonlinear mechanical plants. The paper uses a Fuzzy-Neural Hierarchical Multi-Model (FNHMM), which merge the fuzzy model flexibility with the learning abilities of the RNNs. The paper proposed the application of two control schemes, which are: a trajectory tracking control by an inverse FNHMM and a direct adaptive control, using the states issued by the identification FNHMM. The proposed control methods are applied for a mechanical plant with friction system control, where the obtained comparative results show that the control using FNHMM outperforms the fuzzy and the neural single control.

References

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Paper Citation


in Harvard Style

Baruch I., Luis Olivares J. and Thomas F. (2005). A HIERARCHICAL FUZZY-NEURAL MULTI-MODEL - An application for a mechanical system with friccion identification and control . In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 972-8865-29-5, pages 230-235. DOI: 10.5220/0001174702300235


in Bibtex Style

@conference{icinco05,
author={Ieroham Baruch and Jose Luis Olivares and Federico Thomas},
title={A HIERARCHICAL FUZZY-NEURAL MULTI-MODEL - An application for a mechanical system with friccion identification and control},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2005},
pages={230-235},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001174702300235},
isbn={972-8865-29-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - A HIERARCHICAL FUZZY-NEURAL MULTI-MODEL - An application for a mechanical system with friccion identification and control
SN - 972-8865-29-5
AU - Baruch I.
AU - Luis Olivares J.
AU - Thomas F.
PY - 2005
SP - 230
EP - 235
DO - 10.5220/0001174702300235