Using a Neural Network Trained Only on Integer Order Systems to Identify Fractional Order Dynamics in Networked Systems

Document Type

Conference Proceeding

Publication Date

1-1-2024

Abstract

This paper presents a feed forward artificial neural network that identifies the order of the dynamics of a unit step response. The main contribution of this paper is demonstrating that a system trained on only integer order (first and second order) systems can identify fractional order responses with a high degree of accuracy. The details of the design of structure of the neural network, the training method and the training sets, as well as statistics describing the accuracy of the fractional predictions are presented. Also using the neural network to identify fractional dynamics for a large scale networked system from the authors' prior work is presented as further validation and a demonstration of the applicability of the results. This demonstrates the potential for practicing engineers to use similar machine learning tools trained on "standard"systems with the ability to distinguish when features such as fractional order dynamics are significant and warrant deeper consideration for the design or control of such a system.

Publication Title

10th 2024 International Conference on Control, Decision and Information Technologies, CoDIT 2024

ISBN

[9798350373974]

Link to Full Text

Share

COinS