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Continuous time subspace identification by using laguerre filter and instrumental variable/Siti Fairuz Rokman

Continuous time subspace identification by using laguerre filter and instrumental variable_Siti Fairuz Rokman_E3_2011_NI
Tesis ini mengetengahkan kaedah pengenalpastian ruang bagi sistem masa berterusan dengan menggunakan penapis Laguerre dan pembolehubah instrumen. Pendekatan berpandukan data dalam bentuk subruang telah digunakan untuk mengembangkan model. Tesis ini memberi fokus kepada pengenalpastian sistem masa berterusan bagi sistem gelung terbuka sahaja. Rangkaian penapis Laguerre dan pembolehubah instrumen telah digunakan dalam merangka pengenalpastian model subruang. Penapis Laguerre memainkan peranan yang penting untuk mengelak sebarang permasalahan yang timbul sewaktu operasi pembezaan bagi operasi Laplace. Ia juga mempunyai kebolehan untuk mengatasi masalah hingar pada julat frekuensi yang tinggi disebabkan fungsi ortogonalitinya. Pembolehubah instrumen pula membantu menghapuskan hingar proses dan hingar pengukuran yang mungkin wujud di dalam sistem. Kombinasi teknik-teknik ini telah berjaya menganggar kualiti model yang lebih baik, yang mana, telah berjaya meningkatkan prestasi pengenalpastian sistem masa berterusan secara keseluruhan. ___________________________________________________________________________________ This thesis presents the subspace identification of continuous time system by using Laguerre filter and instrumental variable. A data-driven approach in realization by the subspace method is carried out in developing the models. In this thesis, the approach by subspace method is focused only on open-loop continuous time system identification. The Laguerre filter and the instrumental variables are adopted in the framework of subspace model identification. The main function of Laguerre filter is to avoid problem when dealing with differentiation in the Laplace operator. It has the ability to cope with noise at high frequency region due to its orthogonality function. The instrumental variable helps to eliminate the process and measurement noise that may occur in the system. In this thesis, the combination of these techniques allows for the estimation of high quality models, in which, it leads to successful performance of the continuous time system identification overall.
Contributor(s):
Siti Fairuz Rokman - Author
Primary Item Type:
Final Year Project
Language:
English
Subject Keywords:
subspace ; identification ; filter
First presented to the public:
3/1/2005
Original Publication Date:
2/24/2020
Previously Published By:
Universiti Sains Malaysia
Place Of Publication:
School of Electrical & Electronic Engineering
Citation:
Extents:
Number of Pages - 100
License Grantor / Date Granted:
  / ( View License )
Date Deposited
2020-02-25 16:46:50.081
Submitter:
Nor Hayati Ismail

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