Curve tracking of nonlinear dynamic system using linear state-space model

In this paper, curve tracking of nonlinear dynamic systems is discussed. In mathematical modelling, a curve is defined as the solution of a dynamic system. Assuming the actual model of a dynamic system is unknown, we only have the solution curve of a system. Hence, tracking the curve becomes promine...

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Main Authors: Sie, Long Kek, Wah, June Leong, Lian Kon, Cynthia Mui
Format: Conference or Workshop Item
Language:en
Published: 2024
Subjects:
Online Access:http://eprints.uthm.edu.my/11921/1/P17008_51190508179270c8b980690a1d15b495.pdf%205.pdf
http://eprints.uthm.edu.my/11921/
https://doi.org/10.11159/cdsr24.141
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author Sie, Long Kek
Wah, June Leong
Lian Kon, Cynthia Mui
author_facet Sie, Long Kek
Wah, June Leong
Lian Kon, Cynthia Mui
author_sort Sie, Long Kek
building UTHM Library
collection Institutional Repository
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
continent Asia
country Malaysia
description In this paper, curve tracking of nonlinear dynamic systems is discussed. In mathematical modelling, a curve is defined as the solution of a dynamic system. Assuming the actual model of a dynamic system is unknown, we only have the solution curve of a system. Hence, tracking the curve becomes prominent in studying a nonlinear dynamic system. For this purpose, we propose a linear state-space model to track the curve of a nonlinear dynamic system. First, a least squares optimization problem is introduced, where the differences between the system and the linear model are defined. An adaptive parameter is introduced in the linear model, aiming to capture these differences. Second, the first-order necessary condition is derived, and the adaptive parameter is determined to update the curve of the linear model. Once convergence is achieved, the optimal solution curve of the linear model approximates the correct solution curve of the nonlinear system despite model-reality differences. Third, an example of a chemical kinetics system is studied for illustration. The simulation results show the efficiency of the computation algorithm, and the iterative solution demonstrates the accuracy of curve tracking. Therefore, using the linear state-space model to track the curve of the nonlinear dynamic system is satisfactorily handled
format Conference or Workshop Item
id my.uthm.eprints-11921
institution Universiti Tun Hussein Onn Malaysia
language en
publishDate 2024
record_format eprints
spelling my.uthm.eprints-119212024-12-23T01:51:47Z http://eprints.uthm.edu.my/11921/ Curve tracking of nonlinear dynamic system using linear state-space model Sie, Long Kek Wah, June Leong Lian Kon, Cynthia Mui QA Mathematics In this paper, curve tracking of nonlinear dynamic systems is discussed. In mathematical modelling, a curve is defined as the solution of a dynamic system. Assuming the actual model of a dynamic system is unknown, we only have the solution curve of a system. Hence, tracking the curve becomes prominent in studying a nonlinear dynamic system. For this purpose, we propose a linear state-space model to track the curve of a nonlinear dynamic system. First, a least squares optimization problem is introduced, where the differences between the system and the linear model are defined. An adaptive parameter is introduced in the linear model, aiming to capture these differences. Second, the first-order necessary condition is derived, and the adaptive parameter is determined to update the curve of the linear model. Once convergence is achieved, the optimal solution curve of the linear model approximates the correct solution curve of the nonlinear system despite model-reality differences. Third, an example of a chemical kinetics system is studied for illustration. The simulation results show the efficiency of the computation algorithm, and the iterative solution demonstrates the accuracy of curve tracking. Therefore, using the linear state-space model to track the curve of the nonlinear dynamic system is satisfactorily handled 2024-06-10 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/11921/1/P17008_51190508179270c8b980690a1d15b495.pdf%205.pdf Sie, Long Kek and Wah, June Leong and Lian Kon, Cynthia Mui (2024) Curve tracking of nonlinear dynamic system using linear state-space model. In: Proceedings of the 11th International Conference of Control Systems, and Robotics (CDSR 2024). https://doi.org/10.11159/cdsr24.141
spellingShingle QA Mathematics
Sie, Long Kek
Wah, June Leong
Lian Kon, Cynthia Mui
Curve tracking of nonlinear dynamic system using linear state-space model
title Curve tracking of nonlinear dynamic system using linear state-space model
title_full Curve tracking of nonlinear dynamic system using linear state-space model
title_fullStr Curve tracking of nonlinear dynamic system using linear state-space model
title_full_unstemmed Curve tracking of nonlinear dynamic system using linear state-space model
title_short Curve tracking of nonlinear dynamic system using linear state-space model
title_sort curve tracking of nonlinear dynamic system using linear state-space model
topic QA Mathematics
url http://eprints.uthm.edu.my/11921/1/P17008_51190508179270c8b980690a1d15b495.pdf%205.pdf
http://eprints.uthm.edu.my/11921/
https://doi.org/10.11159/cdsr24.141
url_provider http://eprints.uthm.edu.my/