Kalman Filter-based Estimators for Dual Adaptive Neural Control - A Comparative Analysis of Execution Time and Performance Issues

Simon G. Fabri, Marvin K. Bugeja

2013

Abstract

The real time implementation of neural network-based dual adaptive control for nonlinear systems can become significantly demanding because of the amount of network parameters requiring estimation. This paper explores the effect of three different estimation algorithms for dual adaptive control of a class of multiple-input, multiple-output nonlinear systems in terms of tracking performance and execution time. It is shown that the Unscented and Square-root Unscented Kalman filter estimators lead to a significant improvement in tracking performance when compared with the Extended Kalman filter, but with an appreciable increase in execution time. Such issues need to be given due consideration when implementing controllers for on-line operation.

Paper Citation

in Harvard Style

Fabri S. and Bugeja M. (2013). Kalman Filter-based Estimators for Dual Adaptive Neural Control - A Comparative Analysis of Execution Time and Performance Issues . In Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-8565-70-9, pages 169-176. DOI: 10.5220/0004455601690176

in Bibtex Style

@conference{icinco13,
author={Simon G. Fabri and Marvin K. Bugeja},
title={Kalman Filter-based Estimators for Dual Adaptive Neural Control - A Comparative Analysis of Execution Time and Performance Issues},
booktitle={Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2013},
pages={169-176},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004455601690176},
isbn={978-989-8565-70-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Kalman Filter-based Estimators for Dual Adaptive Neural Control - A Comparative Analysis of Execution Time and Performance Issues
SN - 978-989-8565-70-9
AU - Fabri S.
AU - Bugeja M.
PY - 2013
SP - 169
EP - 176
DO - 10.5220/0004455601690176