Comparative analysis of multiple neural networks for online identification of a UAV

Authors:
Vishwas Puttige;Sreenatha Anavatti;Tapabrata Ray
Affiliations:
School of ACME, UNSW@ADFA, Canberra, Australia;School of ACME, UNSW@ADFA, Canberra, Australia;School of ACME, UNSW@ADFA, Canberra, Australia
Venue:
AI'07 Proceedings of the 20th Australian joint conference on Advances in artificial intelligence
Year:
2007

Citing 2
Cited 0

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Real-Time Neural Network Based Online Identification Technique for a UAV Platform

CIMCA '06 Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce

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Abstract

This paper sumarises a comparative study of multiple neural networks as applied for the identification of the dynamics of an Unmanned Aerial Vehicle (UAV). Each of the networks are based on non-linear autoregressive technique and are trained online. Variations in the architecture, batch size and the initial weights of the multi-network are analysed. A dynamic selection mechanism optimally chooses the most suitable output from the host of networks based on a selection criteria.