Modeling and Identification of Nonlinear DC Motor Drive Systems Using Recurrent Wavelet Networks

A Master of Science thesis in Electrical Engineering by Sarah Hussain Zahidi entitled, "Modeling and Identification of Nonlinear DC Motor Drive Systems Using Recurrent Wavelet Networks," submitted in January 2013. Thesis advisor is Dr. Rached Dhaouadi. Available are both soft and hard copi...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Zahidi, Sarah Hussain (author)
التنسيق: doctoralThesis
منشور في: 2013
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/11073/4818
الوسوم: إضافة وسم
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author Zahidi, Sarah Hussain
author_facet Zahidi, Sarah Hussain
author_role author
dc.contributor.none.fl_str_mv Dhaouadi, Rached
dc.creator.none.fl_str_mv Zahidi, Sarah Hussain
dc.date.none.fl_str_mv 2013-02-10T06:43:32Z
2013-02-10T06:43:32Z
2013-01
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 35.232-2013.04
http://hdl.handle.net/11073/4818
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv recurrent wavelet networks
DC motor parameter identification
friction identification
adaptive learning rates
System analysis
Nonlinear control theory
Dynamics
dc.title.none.fl_str_mv Modeling and Identification of Nonlinear DC Motor Drive Systems Using Recurrent Wavelet Networks
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Electrical Engineering by Sarah Hussain Zahidi entitled, "Modeling and Identification of Nonlinear DC Motor Drive Systems Using Recurrent Wavelet Networks," submitted in January 2013. Thesis advisor is Dr. Rached Dhaouadi. Available are both soft and hard copies of the thesis.
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oai_identifier_str oai:repository.aus.edu:11073/4818
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spelling Modeling and Identification of Nonlinear DC Motor Drive Systems Using Recurrent Wavelet NetworksZahidi, Sarah Hussainrecurrent wavelet networksDC motor parameter identificationfriction identificationadaptive learning ratesSystem analysisNonlinear control theoryDynamicsA Master of Science thesis in Electrical Engineering by Sarah Hussain Zahidi entitled, "Modeling and Identification of Nonlinear DC Motor Drive Systems Using Recurrent Wavelet Networks," submitted in January 2013. Thesis advisor is Dr. Rached Dhaouadi. Available are both soft and hard copies of the thesis.The main objective of this research is to study the use of Recurrent Wavelet Networks (RWN) for the modelling and identification of nonlinear dynamic systems. Since the vast majority of physical processes and systems exhibit nonlinearities in their behavior, mathematical models may be difficult to obtain as processes may be affected by external operating conditions and a number of parameters may not be identified. Electromechanical systems are an example of nonlinear systems where parameters such as viscous and coulomb friction, and distributed inertias are often unknown. In such cases, a model is required that will capture the nonlinearities and the dynamics of the system. In this thesis, an online identification method is developed using structured Recurrent Wavelet Networks (RWN) in order to simultaneously identify linear and nonlinear mechanical parameters of an electromechanical system. Network learning is implemented using the gradient descent algorithm. Stability analysis is carried out based on the minimization of a Lyapunov function in order to obtain Adaptive Learning Rates (ALR) for training the network. Simulations are carried out to validate the performance of the proposed adaptive learning rate based modeling and identification technique. Search Terms: Wavelet Networks, Recurrent Wavelet Networks, DC Motor Parameter Identification, Friction Identification, Adaptive Learning RatesCollege of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE)Dhaouadi, Rached2013-02-10T06:43:32Z2013-02-10T06:43:32Z2013-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2013.04http://hdl.handle.net/11073/4818en_USoai:repository.aus.edu:11073/48182025-06-26T12:31:05Z
spellingShingle Modeling and Identification of Nonlinear DC Motor Drive Systems Using Recurrent Wavelet Networks
Zahidi, Sarah Hussain
recurrent wavelet networks
DC motor parameter identification
friction identification
adaptive learning rates
System analysis
Nonlinear control theory
Dynamics
status_str publishedVersion
title Modeling and Identification of Nonlinear DC Motor Drive Systems Using Recurrent Wavelet Networks
title_full Modeling and Identification of Nonlinear DC Motor Drive Systems Using Recurrent Wavelet Networks
title_fullStr Modeling and Identification of Nonlinear DC Motor Drive Systems Using Recurrent Wavelet Networks
title_full_unstemmed Modeling and Identification of Nonlinear DC Motor Drive Systems Using Recurrent Wavelet Networks
title_short Modeling and Identification of Nonlinear DC Motor Drive Systems Using Recurrent Wavelet Networks
title_sort Modeling and Identification of Nonlinear DC Motor Drive Systems Using Recurrent Wavelet Networks
topic recurrent wavelet networks
DC motor parameter identification
friction identification
adaptive learning rates
System analysis
Nonlinear control theory
Dynamics
url http://hdl.handle.net/11073/4818