Identification Of Multivariable Ill-Conditioned Sysrems Using Virtual Transfer Function Between Inputs

In industry, processes are often multivariable, and frequently possess strong interactions among the various outputs. Such systems will be ill-conditioned due to the presence of high and low gain directions. The system will respond much more strongly if the input lies in the former than the latter....

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Main Author:	Yap, Timothy Tzen Vun
Format:	Thesis
Published:	2016
Subjects:	QA801-939 Analytic mechanics
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id	my-mmu-ep.7171
record_format	uketd_dc
spelling	my-mmu-ep.71712018-07-06T13:36:36Z Identification Of Multivariable Ill-Conditioned Sysrems Using Virtual Transfer Function Between Inputs 2016-08 Yap, Timothy Tzen Vun QA801-939 Analytic mechanics In industry, processes are often multivariable, and frequently possess strong interactions among the various outputs. Such systems will be ill-conditioned due to the presence of high and low gain directions. The system will respond much more strongly if the input lies in the former than the latter. Therefore, it is necessary for perturbation signals designed for ill-conditioned systems to sufficiently excite the low gain direction for accurate identification, especially of the smallest singular value. In view of this, the virtual transfer function between inputs (VTFBI) perturbation signal design is introduced with the aim of improving the accuracy in estimating the smallest singular value. The design takes into account the uniform excitation of all output directions with as large an output signal-to-noise ratio (SNR) as possible, subject to power constraints at the input and possible bounds at the output. Starting with a 2×2 system, the theoretical formulation of the VTFBI is developed. The VTFBI technique utilises a single correlated harmonic chosen at a frequency where the system gain is expected to be reasonably large. The relation between the outputs are made to describe a circle so that equal perturbation in all output directions is achieved, through design parameters that include the relative magnitudes and phases of the chosen correlated harmonic using information of the system’s gains and phases obtained from an a priori test. 2016-08 Thesis http://shdl.mmu.edu.my/7171/ http://library.mmu.edu.my/diglib/onlinedb/dig_lib.php phd doctoral Multimedia University Faculty of Engineering
institution	Multimedia University
collection	MMU Institutional Repository
topic	QA801-939 Analytic mechanics
spellingShingle	QA801-939 Analytic mechanics Yap, Timothy Tzen Vun Identification Of Multivariable Ill-Conditioned Sysrems Using Virtual Transfer Function Between Inputs
description	In industry, processes are often multivariable, and frequently possess strong interactions among the various outputs. Such systems will be ill-conditioned due to the presence of high and low gain directions. The system will respond much more strongly if the input lies in the former than the latter. Therefore, it is necessary for perturbation signals designed for ill-conditioned systems to sufficiently excite the low gain direction for accurate identification, especially of the smallest singular value. In view of this, the virtual transfer function between inputs (VTFBI) perturbation signal design is introduced with the aim of improving the accuracy in estimating the smallest singular value. The design takes into account the uniform excitation of all output directions with as large an output signal-to-noise ratio (SNR) as possible, subject to power constraints at the input and possible bounds at the output. Starting with a 2×2 system, the theoretical formulation of the VTFBI is developed. The VTFBI technique utilises a single correlated harmonic chosen at a frequency where the system gain is expected to be reasonably large. The relation between the outputs are made to describe a circle so that equal perturbation in all output directions is achieved, through design parameters that include the relative magnitudes and phases of the chosen correlated harmonic using information of the system’s gains and phases obtained from an a priori test.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Yap, Timothy Tzen Vun
author_facet	Yap, Timothy Tzen Vun
author_sort	Yap, Timothy Tzen Vun
title	Identification Of Multivariable Ill-Conditioned Sysrems Using Virtual Transfer Function Between Inputs
title_short	Identification Of Multivariable Ill-Conditioned Sysrems Using Virtual Transfer Function Between Inputs
title_full	Identification Of Multivariable Ill-Conditioned Sysrems Using Virtual Transfer Function Between Inputs
title_fullStr	Identification Of Multivariable Ill-Conditioned Sysrems Using Virtual Transfer Function Between Inputs
title_full_unstemmed	Identification Of Multivariable Ill-Conditioned Sysrems Using Virtual Transfer Function Between Inputs
title_sort	identification of multivariable ill-conditioned sysrems using virtual transfer function between inputs
granting_institution	Multimedia University
granting_department	Faculty of Engineering
publishDate	2016
_version_	1747829659215593472

Identification Of Multivariable Ill-Conditioned Sysrems Using Virtual Transfer Function Between Inputs

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