Discrete-Time System Identification Based On Novel Information Criterion Using Genetic Algorithm

Abd Samad, Md Fahmi and Mohd Nasir, A. R. (2017) Discrete-Time System Identification Based On Novel Information Criterion Using Genetic Algorithm. Journal Of Fundamental And Applied Sciences, 9 (7S). pp. 584-599. ISSN 1112-9867

[img] Text
3353-7186-1-PB_MMETIC_JFAS.pdf - Accepted Version

Download (499kB)

Abstract

Model structure selection is a problem in system identification which addresses selecting an adequate model i.e. a model that has a good balance between parsimony and accuracy in approximating a dynamic system. Parameter magnitude-based information criterion 2 (PMIC2), as a novel information criterion, is used alongside Akaike information criterion (AIC). Genetic algorithm (GA) as a popular search method, is used for selecting a model structure. The advantage of using GA is in reduction of computational burden. This paper investigates the identification of dynamic system in the form of NARX (Non-linear AutoRegressive with eXogenous input) model based on PMIC2 and AIC using GA. This shall be tested using computational software on a number of simulated systems. As a conclusion, PMIC2 is able to select optimum model structure better than AIC.

Item Type: Article
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics
Divisions: Faculty of Mechanical Engineering > Department of Structure and Materials
Depositing User: Mohd Hannif Jamaludin
Date Deposited: 12 Mar 2019 07:40
Last Modified: 29 Jun 2021 17:25
URI: http://eprints.utem.edu.my/id/eprint/22715
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item