INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM

The gradient flexible plate structure has been widely used in engineering industries. However, the gradient flexible plate is susceptible to vibrational disturbances and affecting its durability and performance over time. Hence, the unwanted vibration needs to be controlled and can be accomplished b...

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Main Author:	Muhammad Hasbollah, Hassan
Format:	Thesis
Language:	English
Published:	2023
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://ir.unimas.my/id/eprint/41752/1/Intelligent%20Modelling%20of%20Gradient%20Flexible%20Plate%20Structure%20Utilising%20Hybrid%20Evolutionary%20Algorithm.pdf
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id	my-unimas-ir.41752
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spelling	my-unimas-ir.417522023-05-03T07:24:37Z INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM 2023-05-02 Muhammad Hasbollah, Hassan TJ Mechanical engineering and machinery The gradient flexible plate structure has been widely used in engineering industries. However, the gradient flexible plate is susceptible to vibrational disturbances and affecting its durability and performance over time. Hence, the unwanted vibration needs to be controlled and can be accomplished by developing an accurate model. Despite that, the accurate model is hard to be obtained especially in estimating the model parameters. Thus, the research presents the development of dynamic modelling for gradient flexible plate structure (GFPS). A slanted GFPS with orientation angle of 30° and all edges clamped was developed and fabricated to represent the actual dynamics of the system. Then, data acquisition and instrumentation system were integrated to the rig to collect the input-output vibration data. The research utilised parametric system identification based on autoregressive with exogenous input (ARX) model structure. First, evolutionary algorithms, namely particle swarm optimisation (PSO) and grey wolf optimisation (GWO) were used in developing GFPS dynamic model and their performances were compared. It was discovered that GWO model outperformed PSO model. However, the computational time of GWO is slower compared to PSO. Thus, a hybrid of grey wolf and particle swarm optimisation (GWO-PSO) were proposed to further improve the system modelling. It was found out that the hybrid GWO-PSO model outperformed PSO and GWO models by achieving the lowest mean squared error, correlation up to 95 % confidence level, and good stability. The obtained GWO-PSO models which is model order 2 and model order 4 were verified by using proportional-integral-derivative (PID) based controller. Their performances were measured in terms of model robustness based on vibration suppression. The final result confirmed that model order 2 of GWO-PSO is the optimum model to represent GFPS system modelling with 71.08% vibration attenuation. Universiti Malaysia Sarawak 2023-05 Thesis http://ir.unimas.my/id/eprint/41752/ http://ir.unimas.my/id/eprint/41752/1/Intelligent%20Modelling%20of%20Gradient%20Flexible%20Plate%20Structure%20Utilising%20Hybrid%20Evolutionary%20Algorithm.pdf text en public masters Universiti Malaysia Sarawak Faculty of Engineering
institution	Universiti Malaysia Sarawak
collection	UNIMAS Institutional Repository
language	English
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery Muhammad Hasbollah, Hassan INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM
description	The gradient flexible plate structure has been widely used in engineering industries. However, the gradient flexible plate is susceptible to vibrational disturbances and affecting its durability and performance over time. Hence, the unwanted vibration needs to be controlled and can be accomplished by developing an accurate model. Despite that, the accurate model is hard to be obtained especially in estimating the model parameters. Thus, the research presents the development of dynamic modelling for gradient flexible plate structure (GFPS). A slanted GFPS with orientation angle of 30° and all edges clamped was developed and fabricated to represent the actual dynamics of the system. Then, data acquisition and instrumentation system were integrated to the rig to collect the input-output vibration data. The research utilised parametric system identification based on autoregressive with exogenous input (ARX) model structure. First, evolutionary algorithms, namely particle swarm optimisation (PSO) and grey wolf optimisation (GWO) were used in developing GFPS dynamic model and their performances were compared. It was discovered that GWO model outperformed PSO model. However, the computational time of GWO is slower compared to PSO. Thus, a hybrid of grey wolf and particle swarm optimisation (GWO-PSO) were proposed to further improve the system modelling. It was found out that the hybrid GWO-PSO model outperformed PSO and GWO models by achieving the lowest mean squared error, correlation up to 95 % confidence level, and good stability. The obtained GWO-PSO models which is model order 2 and model order 4 were verified by using proportional-integral-derivative (PID) based controller. Their performances were measured in terms of model robustness based on vibration suppression. The final result confirmed that model order 2 of GWO-PSO is the optimum model to represent GFPS system modelling with 71.08% vibration attenuation.
format	Thesis
qualification_level	Master's degree
author	Muhammad Hasbollah, Hassan
author_facet	Muhammad Hasbollah, Hassan
author_sort	Muhammad Hasbollah, Hassan
title	INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM
title_short	INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM
title_full	INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM
title_fullStr	INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM
title_full_unstemmed	INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM
title_sort	intelligent modelling of gradient flexible plate structure utilising hybrid evolutionary algorithm
granting_institution	Universiti Malaysia Sarawak
granting_department	Faculty of Engineering
publishDate	2023
url	http://ir.unimas.my/id/eprint/41752/1/Intelligent%20Modelling%20of%20Gradient%20Flexible%20Plate%20Structure%20Utilising%20Hybrid%20Evolutionary%20Algorithm.pdf
_version_	1783728530119458816

INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM

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