Multi-objective opimization of MIMO control system using surrogate modeling

A multi-objective optimization approach using surrogate modeling is applied to a nonlinear Multi Input Multi Outputs (MIMO) control system model to predict Pareto-front of objective functions which is defined using Integral Square Error (ISE). Typically, practical multi-objective optimization was hi...

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Main Author:	Nor Shah, Mohd. Fauzi
Format:	Thesis
Language:	English
Published:	2012
Subjects:	Unspecified
Online Access:	http://eprints.utm.my/id/eprint/32309/1/MohdFauziNorShahMFKE2012.pdf
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id	my-utm-ep.32309
record_format	uketd_dc
spelling	my-utm-ep.323092017-09-20T08:45:58Z Multi-objective opimization of MIMO control system using surrogate modeling 2012-12 Nor Shah, Mohd. Fauzi Unspecified A multi-objective optimization approach using surrogate modeling is applied to a nonlinear Multi Input Multi Outputs (MIMO) control system model to predict Pareto-front of objective functions which is defined using Integral Square Error (ISE). Typically, practical multi-objective optimization was highly expensive even in computer simulation. To address such a challenge, approximation or surrogate based techniques are adopted to reduce the computational cost. The surrogate modeling developed as surrogates of the expensive simulation process in order to improve the overall computation efficiency in multi-objective optimization problem. By using surrogate modeling, the location of the actual Pareto-front is predicted by Radial Basis Function Neural Network (RBFNN) using only a small fraction of the design space. Some case studies show that the surrogate modeling manages to predict most of the Pareto-front of the design space. The best compromise of ISE obtained from predicted Pareto-front produces optimum response for MIMO control system. The result indicates that the procedure to construct the ‘model of the model’ totally compensates the computational expense. This thesis also demonstrates that there are a number of techniques which can be used to tackle difficult multi-objective problems. 2012-12 Thesis http://eprints.utm.my/id/eprint/32309/ http://eprints.utm.my/id/eprint/32309/1/MohdFauziNorShahMFKE2012.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	Unspecified
spellingShingle	Unspecified Nor Shah, Mohd. Fauzi Multi-objective opimization of MIMO control system using surrogate modeling
description	A multi-objective optimization approach using surrogate modeling is applied to a nonlinear Multi Input Multi Outputs (MIMO) control system model to predict Pareto-front of objective functions which is defined using Integral Square Error (ISE). Typically, practical multi-objective optimization was highly expensive even in computer simulation. To address such a challenge, approximation or surrogate based techniques are adopted to reduce the computational cost. The surrogate modeling developed as surrogates of the expensive simulation process in order to improve the overall computation efficiency in multi-objective optimization problem. By using surrogate modeling, the location of the actual Pareto-front is predicted by Radial Basis Function Neural Network (RBFNN) using only a small fraction of the design space. Some case studies show that the surrogate modeling manages to predict most of the Pareto-front of the design space. The best compromise of ISE obtained from predicted Pareto-front produces optimum response for MIMO control system. The result indicates that the procedure to construct the ‘model of the model’ totally compensates the computational expense. This thesis also demonstrates that there are a number of techniques which can be used to tackle difficult multi-objective problems.
format	Thesis
qualification_level	Master's degree
author	Nor Shah, Mohd. Fauzi
author_facet	Nor Shah, Mohd. Fauzi
author_sort	Nor Shah, Mohd. Fauzi
title	Multi-objective opimization of MIMO control system using surrogate modeling
title_short	Multi-objective opimization of MIMO control system using surrogate modeling
title_full	Multi-objective opimization of MIMO control system using surrogate modeling
title_fullStr	Multi-objective opimization of MIMO control system using surrogate modeling
title_full_unstemmed	Multi-objective opimization of MIMO control system using surrogate modeling
title_sort	multi-objective opimization of mimo control system using surrogate modeling
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2012
url	http://eprints.utm.my/id/eprint/32309/1/MohdFauziNorShahMFKE2012.pdf
_version_	1747815971560620032

Multi-objective opimization of MIMO control system using surrogate modeling

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