Parametric system identification and active vibration control of vibrational structures using genetic algorithm

A vibration system has advantages and disadvantages for us. Some of the disadvantages of the vibration system are discomfort, noise, malfunctioning, wear, fatigue and even destruction. An example of structure that leads to high vibration when subjected to disturbance forces is flexible plate structu...

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Main Author: Mohammad Sofi @ Aziz, Azfi Zaihan
Format: Thesis
Language:English
Published: 2007
Subjects:
Online Access:http://eprints.utm.my/9527/
http://eprints.utm.my/9527/1/AzfiZaihanMFKM2007.pdf
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author Mohammad Sofi @ Aziz, Azfi Zaihan
author_facet Mohammad Sofi @ Aziz, Azfi Zaihan
author_sort Mohammad Sofi @ Aziz, Azfi Zaihan
building UTeM Institutional Repository
collection Online Access
description A vibration system has advantages and disadvantages for us. Some of the disadvantages of the vibration system are discomfort, noise, malfunctioning, wear, fatigue and even destruction. An example of structure that leads to high vibration when subjected to disturbance forces is flexible plate structure. The aim of this research is to develop an Auto Regressive with eXogenous Input (ARX) model characterizing the dynamic behaviour of a two-dimensional (2D) flexible plate structure and the development of active vibration control (AVC) strategies for the structures. In order to construct the model, several sets of vibration data were obtained from the simulation of the flexible plate structures based on finite difference method. The sets of data obtained were utilised to develop ARX model using Least Squares (LS), Recursive Least Squares (RLS) and Genetic Algorithm (GA) methods. The models were validated using one step ahead (OSA) prediction, mean squared error (MSE) and correlation tests. Then, single-input single-output active vibration control (SISO-AVC) was devised using thus developed RLS and GA models. The performance of these systems was assessed in terms of comparison between uncontrolled signals, RLS-AVC and GA-AVC controlled signals in time domain, spectral density and attenuation of the signals in decibel (dB). The results show that GA is the best method in system modeling and vibration control of the simulated 2D flexible plate structures compared to RLS and LS.
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spelling utm-95272018-09-27T04:11:57Z http://eprints.utm.my/9527/ Parametric system identification and active vibration control of vibrational structures using genetic algorithm Mohammad Sofi @ Aziz, Azfi Zaihan TJ Mechanical engineering and machinery A vibration system has advantages and disadvantages for us. Some of the disadvantages of the vibration system are discomfort, noise, malfunctioning, wear, fatigue and even destruction. An example of structure that leads to high vibration when subjected to disturbance forces is flexible plate structure. The aim of this research is to develop an Auto Regressive with eXogenous Input (ARX) model characterizing the dynamic behaviour of a two-dimensional (2D) flexible plate structure and the development of active vibration control (AVC) strategies for the structures. In order to construct the model, several sets of vibration data were obtained from the simulation of the flexible plate structures based on finite difference method. The sets of data obtained were utilised to develop ARX model using Least Squares (LS), Recursive Least Squares (RLS) and Genetic Algorithm (GA) methods. The models were validated using one step ahead (OSA) prediction, mean squared error (MSE) and correlation tests. Then, single-input single-output active vibration control (SISO-AVC) was devised using thus developed RLS and GA models. The performance of these systems was assessed in terms of comparison between uncontrolled signals, RLS-AVC and GA-AVC controlled signals in time domain, spectral density and attenuation of the signals in decibel (dB). The results show that GA is the best method in system modeling and vibration control of the simulated 2D flexible plate structures compared to RLS and LS. 2007-11 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/9527/1/AzfiZaihanMFKM2007.pdf Mohammad Sofi @ Aziz, Azfi Zaihan (2007) Parametric system identification and active vibration control of vibrational structures using genetic algorithm. Masters thesis, Universiti Teknologi Malaysia, Faculty of Mechanical Engineering.
spellingShingle TJ Mechanical engineering and machinery
Mohammad Sofi @ Aziz, Azfi Zaihan
Parametric system identification and active vibration control of vibrational structures using genetic algorithm
title Parametric system identification and active vibration control of vibrational structures using genetic algorithm
title_full Parametric system identification and active vibration control of vibrational structures using genetic algorithm
title_fullStr Parametric system identification and active vibration control of vibrational structures using genetic algorithm
title_full_unstemmed Parametric system identification and active vibration control of vibrational structures using genetic algorithm
title_short Parametric system identification and active vibration control of vibrational structures using genetic algorithm
title_sort parametric system identification and active vibration control of vibrational structures using genetic algorithm
topic TJ Mechanical engineering and machinery
url http://eprints.utm.my/9527/
http://eprints.utm.my/9527/1/AzfiZaihanMFKM2007.pdf