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Case study : Comparison between statics and dynamics neural network model of nonlinear system identification

This project is predominantly research based project. Literature review of various types and characteristics of nonlinear system and nonlinear system identification was done. Neural network was chosen as the method for system identification. After studying the characteristics of the nonlinear system...

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Main Author: Akmal Asyraf Bin Tik
Format: text::Thesis
Language:English
Published: 2023
Subjects:
System identification
Neural network (Computer science)
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spelling my.uniten.dspace-209162023-05-05T12:40:49Z Case study : Comparison between statics and dynamics neural network model of nonlinear system identification Akmal Asyraf Bin Tik System identification Neural network (Computer science) This project is predominantly research based project. Literature review of various types and characteristics of nonlinear system and nonlinear system identification was done. Neural network was chosen as the method for system identification. After studying the characteristics of the nonlinear system, a nonlinear model was chosen based on the mathematical equation of the system. A Simulink model of the system was constructed based on the mathematical expression of the nonlinear model. The purpose of building this model is to collect the data in order to analyze the model later. Since the output of nonlinear system is differ for every simulation, it is important to have the same input and output data pair for every analysis. 2023-05-03T15:34:20Z 2023-05-03T15:34:20Z 2008 Resource Types::text::Thesis https://irepository.uniten.edu.my/handle/123456789/20916 en application/pdf
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
topic System identification
Neural network (Computer science)
spellingShingle System identification
Neural network (Computer science)
Akmal Asyraf Bin Tik
Case study : Comparison between statics and dynamics neural network model of nonlinear system identification
description This project is predominantly research based project. Literature review of various types and characteristics of nonlinear system and nonlinear system identification was done. Neural network was chosen as the method for system identification. After studying the characteristics of the nonlinear system, a nonlinear model was chosen based on the mathematical equation of the system. A Simulink model of the system was constructed based on the mathematical expression of the nonlinear model. The purpose of building this model is to collect the data in order to analyze the model later. Since the output of nonlinear system is differ for every simulation, it is important to have the same input and output data pair for every analysis.
format Resource Types::text::Thesis
author Akmal Asyraf Bin Tik
author_facet Akmal Asyraf Bin Tik
author_sort Akmal Asyraf Bin Tik
title Case study : Comparison between statics and dynamics neural network model of nonlinear system identification
title_short Case study : Comparison between statics and dynamics neural network model of nonlinear system identification
title_full Case study : Comparison between statics and dynamics neural network model of nonlinear system identification
title_fullStr Case study : Comparison between statics and dynamics neural network model of nonlinear system identification
title_full_unstemmed Case study : Comparison between statics and dynamics neural network model of nonlinear system identification
title_sort case study : comparison between statics and dynamics neural network model of nonlinear system identification
publishDate 2023
_version_ 1806428164142923776
score 13.222552

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