Identification of continuous-time hammerstein system using sine cosine algorithm
This paper presents the development of identification of continuous-time Hammerstein systems based on Sine Cosine Algorithm (SCA). Here, the structure of the nonlinear subsystem is assumed to be unknown, while the structure of the linear subsystem which is the system order assumed to be available. T...
Saved in:
Main Authors: | , , , |
---|---|
Format: | Conference or Workshop Item |
Language: | English English |
Published: |
IEEE
2019
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/27134/1/39.%20Identification%20of%20continuous-time%20hammerstein%20system%20using%20sine%20cosine%20algorithm.pdf http://umpir.ump.edu.my/id/eprint/27134/2/39.1%20Identification%20of%20continuous-time%20hammerstein%20system%20using%20sine%20cosine%20algorithm.pdf http://umpir.ump.edu.my/id/eprint/27134/ https://doi.org/10.1109/ICSIMA47653.2019.9057299 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.ump.umpir.27134 |
---|---|
record_format |
eprints |
spelling |
my.ump.umpir.271342020-07-28T04:37:28Z http://umpir.ump.edu.my/id/eprint/27134/ Identification of continuous-time hammerstein system using sine cosine algorithm E. F., Junis J. J., Jui Mohd Helmi, Suid Mohd Ashraf, Ahmad TK Electrical engineering. Electronics Nuclear engineering This paper presents the development of identification of continuous-time Hammerstein systems based on Sine Cosine Algorithm (SCA). Here, the structure of the nonlinear subsystem is assumed to be unknown, while the structure of the linear subsystem which is the system order assumed to be available. The SCA based method is then used to estimate the parameters in both the linear and nonlinear parts based on the given input and output data. Two numerical examples are given to illustrate the effectiveness of the SCA based algorithm. A continuous-time Infinite Impulse Response (IIR) filter is considered in the linear part, while the nonlinear functions, such as quadratic and hyperbolic are considered in the nonlinear part. The analysis of the numerical results is observed in terms of the parameter identification error, the convergence curve of the objective function, the output response in the time domain and the linear system response in the frequency domain. The results show that the potential of SCA based algorithm in giving an accurate parameter estimation of the Hammerstein models, especially for low noise level. IEEE 2019 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/27134/1/39.%20Identification%20of%20continuous-time%20hammerstein%20system%20using%20sine%20cosine%20algorithm.pdf pdf en http://umpir.ump.edu.my/id/eprint/27134/2/39.1%20Identification%20of%20continuous-time%20hammerstein%20system%20using%20sine%20cosine%20algorithm.pdf E. F., Junis and J. J., Jui and Mohd Helmi, Suid and Mohd Ashraf, Ahmad (2019) Identification of continuous-time hammerstein system using sine cosine algorithm. In: International Conference on Smart Instrumentation, Measurement and Application 2019, 27-29 August 2019 , Kuala Lumpur, Malaysia. pp. 1-6.. ISSN 2640-6535 ISBN 978-1-7281-3952-4 https://doi.org/10.1109/ICSIMA47653.2019.9057299 |
institution |
Universiti Malaysia Pahang |
building |
UMP Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Malaysia Pahang |
content_source |
UMP Institutional Repository |
url_provider |
http://umpir.ump.edu.my/ |
language |
English English |
topic |
TK Electrical engineering. Electronics Nuclear engineering |
spellingShingle |
TK Electrical engineering. Electronics Nuclear engineering E. F., Junis J. J., Jui Mohd Helmi, Suid Mohd Ashraf, Ahmad Identification of continuous-time hammerstein system using sine cosine algorithm |
description |
This paper presents the development of identification of continuous-time Hammerstein systems based on Sine Cosine Algorithm (SCA). Here, the structure of the nonlinear subsystem is assumed to be unknown, while the structure of the linear subsystem which is the system order assumed to be available. The SCA based method is then used to estimate the parameters in both the linear and nonlinear parts based on the given input and output data. Two numerical examples are given to illustrate the effectiveness of the SCA based algorithm. A continuous-time Infinite Impulse Response (IIR) filter is considered in the linear part, while the nonlinear functions, such as quadratic and hyperbolic are considered in the nonlinear part. The analysis of the numerical results is observed in terms of the parameter identification error, the convergence curve of the objective function, the output response in the time domain and the linear system response in the frequency domain. The results show that the potential of SCA based algorithm in giving an accurate parameter estimation of the Hammerstein models, especially for low noise level. |
format |
Conference or Workshop Item |
author |
E. F., Junis J. J., Jui Mohd Helmi, Suid Mohd Ashraf, Ahmad |
author_facet |
E. F., Junis J. J., Jui Mohd Helmi, Suid Mohd Ashraf, Ahmad |
author_sort |
E. F., Junis |
title |
Identification of continuous-time hammerstein system using sine cosine algorithm |
title_short |
Identification of continuous-time hammerstein system using sine cosine algorithm |
title_full |
Identification of continuous-time hammerstein system using sine cosine algorithm |
title_fullStr |
Identification of continuous-time hammerstein system using sine cosine algorithm |
title_full_unstemmed |
Identification of continuous-time hammerstein system using sine cosine algorithm |
title_sort |
identification of continuous-time hammerstein system using sine cosine algorithm |
publisher |
IEEE |
publishDate |
2019 |
url |
http://umpir.ump.edu.my/id/eprint/27134/1/39.%20Identification%20of%20continuous-time%20hammerstein%20system%20using%20sine%20cosine%20algorithm.pdf http://umpir.ump.edu.my/id/eprint/27134/2/39.1%20Identification%20of%20continuous-time%20hammerstein%20system%20using%20sine%20cosine%20algorithm.pdf http://umpir.ump.edu.my/id/eprint/27134/ https://doi.org/10.1109/ICSIMA47653.2019.9057299 |
_version_ |
1674066374871220224 |
score |
13.160551 |