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MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD

Channel isolation usmg partial correlation analysis and estimation of model parameters in the conventional multivariable closed-loop system identification approaches use the method of Least Square (LS) with the limitations, viz. (I) large estimation bias due to the highly correlated input signals...

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Main Author: MOHAMED OSMAN, MOHAMED ABDELRAHIM
Format: Thesis
Language:English
Published: 2016
Subjects:
TP Chemical technology
Online Access:http://utpedia.utp.edu.my/21904/1/2016%20-CHEMICAL%20-%20MULTIVARIABLE%20CLOSED-LOOP%20SYSTEM%20IDENTIFICATION%20USING%20ITERATIVE%20LEAKY%20LEAST%20MEAN%20SQUARES%20METHOD%20-%20MOHAMED%20ABDELRAHIM%20MOHAMED%20OSMAN.pdf
http://utpedia.utp.edu.my/21904/
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spelling my-utp-utpedia.219042021-09-27T08:26:13Z http://utpedia.utp.edu.my/21904/ MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD MOHAMED OSMAN, MOHAMED ABDELRAHIM TP Chemical technology Channel isolation usmg partial correlation analysis and estimation of model parameters in the conventional multivariable closed-loop system identification approaches use the method of Least Square (LS) with the limitations, viz. (I) large estimation bias due to the highly correlated input signals, low Signal to Noise Ratio (SNR) and correlated noise signals; and (2) inconsistent parameter estimates due to noise and unmeasured disturbances. In this thesis. iterative Leaky Least Mean Squares (LLMS) based methods are proposed to address the limitations ofLS method in MultiInput Multi-Output (MIMO) closed-loop system identification. In this research. novel algorithms have been developed to: (I) isolate the less interacting channe Is using a modified partial correlation algorithm. (2) achieve unbiased and consistent parameter estimates using an iterative LLMS algorithm and (3) develop parsimonious models for closed-loop MIMO systems. All the proposed algorithms are demonstrated with the help of extensive simulation case studies and a real pilot-scale distillation column with appropriate validation procedures. 2016-07 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/21904/1/2016%20-CHEMICAL%20-%20MULTIVARIABLE%20CLOSED-LOOP%20SYSTEM%20IDENTIFICATION%20USING%20ITERATIVE%20LEAKY%20LEAST%20MEAN%20SQUARES%20METHOD%20-%20MOHAMED%20ABDELRAHIM%20MOHAMED%20OSMAN.pdf MOHAMED OSMAN, MOHAMED ABDELRAHIM (2016) MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD. PhD thesis, Universiti Teknologi PETRONAS.
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic TP Chemical technology
spellingShingle TP Chemical technology
MOHAMED OSMAN, MOHAMED ABDELRAHIM
MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD
description Channel isolation usmg partial correlation analysis and estimation of model parameters in the conventional multivariable closed-loop system identification approaches use the method of Least Square (LS) with the limitations, viz. (I) large estimation bias due to the highly correlated input signals, low Signal to Noise Ratio (SNR) and correlated noise signals; and (2) inconsistent parameter estimates due to noise and unmeasured disturbances. In this thesis. iterative Leaky Least Mean Squares (LLMS) based methods are proposed to address the limitations ofLS method in MultiInput Multi-Output (MIMO) closed-loop system identification. In this research. novel algorithms have been developed to: (I) isolate the less interacting channe Is using a modified partial correlation algorithm. (2) achieve unbiased and consistent parameter estimates using an iterative LLMS algorithm and (3) develop parsimonious models for closed-loop MIMO systems. All the proposed algorithms are demonstrated with the help of extensive simulation case studies and a real pilot-scale distillation column with appropriate validation procedures.
format Thesis
author MOHAMED OSMAN, MOHAMED ABDELRAHIM
author_facet MOHAMED OSMAN, MOHAMED ABDELRAHIM
author_sort MOHAMED OSMAN, MOHAMED ABDELRAHIM
title MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD
title_short MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD
title_full MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD
title_fullStr MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD
title_full_unstemmed MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD
title_sort multivariable closed-loop system identification using iterative leaky least mean squares method
publishDate 2016
url http://utpedia.utp.edu.my/21904/1/2016%20-CHEMICAL%20-%20MULTIVARIABLE%20CLOSED-LOOP%20SYSTEM%20IDENTIFICATION%20USING%20ITERATIVE%20LEAKY%20LEAST%20MEAN%20SQUARES%20METHOD%20-%20MOHAMED%20ABDELRAHIM%20MOHAMED%20OSMAN.pdf
http://utpedia.utp.edu.my/21904/
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score 13.211869

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