Modelling and FDI of Dynamic Discrete Time Systems Using a MLP with a New Sigmoidal Activation Function

In this paper we investigate the use of the multi-layer perceptron (MLP) for system modelling. A new sigmoidal activation function is introduced and the study is focused at the utilization of this function on a MLP that performs modelling of dynamic, discrete time systems. The role of the activation...

Full description

Saved in:
Bibliographic Details
Published in:Journal of intelligent & robotic systems 2004-09, Vol.41 (1), p.19-36
Main Authors: Skoundrianos, E N, Tzafestas, S G
Format: Article
Language:English
Subjects:
Activation
Activation analysis
Computer simulation
Discrete time systems
Dynamical systems
Dynamics
Mathematical models
Studies
Tanks
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper we investigate the use of the multi-layer perceptron (MLP) for system modelling. A new sigmoidal activation function is introduced and the study is focused at the utilization of this function on a MLP that performs modelling of dynamic, discrete time systems. The role of the activation function in the training process is investigated analytically, and it is proven that the shape of the activation function and it's derivative can affect the training outcome. The method is simulated at a well known benchmark, namely the three tank system, and is incorporated in a Fault Detection and Identification (FDI) method, also applied and simulated at the three tank system. Finally, a comparison is made with an approach that utilizes local model neural networks for system modeling.[PUBLICATION ABSTRACT]
ISSN:0921-0296
1573-0409
DOI:10.1023/B:JINT.0000049175.78893.2f