Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural Networks

A Master of Science thesis in Mechatronics Submitted to the School of Engineering by Reza Jafari, "Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural Networks," June 2005. Thesis Advisor Dr. Rached Dhaouadi.Available are Both Soft and Hard Copies of the Thesis.

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Jafari, Reza (author)
التنسيق: doctoralThesis
منشور في: 2005
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/11073/100
الوسوم: إضافة وسم
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author Jafari, Reza
author_facet Jafari, Reza
author_role author
dc.contributor.none.fl_str_mv Dhaouadi, Rached
dc.creator.none.fl_str_mv Jafari, Reza
dc.date.none.fl_str_mv 2005-06
2011-03-10T12:43:55Z
2011-03-10T12:43:55Z
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.identifier.none.fl_str_mv 35.232-2005.01
http://hdl.handle.net/11073/100
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv Nonlinear control theory
PID controllers
Mechatronics
Feedforward neural networks
Recurrent neural networks
dc.title.none.fl_str_mv Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural Networks
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Mechatronics Submitted to the School of Engineering by Reza Jafari, "Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural Networks," June 2005. Thesis Advisor Dr. Rached Dhaouadi.Available are Both Soft and Hard Copies of the Thesis.
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oai_identifier_str oai:repository.aus.edu:11073/100
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spelling Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural NetworksJafari, RezaNonlinear control theoryPID controllersMechatronicsFeedforward neural networksRecurrent neural networksA Master of Science thesis in Mechatronics Submitted to the School of Engineering by Reza Jafari, "Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural Networks," June 2005. Thesis Advisor Dr. Rached Dhaouadi.Available are Both Soft and Hard Copies of the Thesis.The main objective of this research is to study feedforeword and recurrent neural networks (RNN) for nonlinear dynamic system identification and control. To be able to control, predict or analyze any system, accurate model is essential. Most real-world applications have inherent nonlinearities. Conventional PID or state feedback controllers are usually not capable of dealing with severe process nonlinearity, variable time delays, time-varying process dynamics and unobservable states. This research work will study RNN based controllers as a viable alternative to handle these difficulties. Due to the intrinsic characteristics of RNNs in having internal memory, they are capable of modeling any linear or nonlinear dynamic system. In this research work we will develop an adaptive RNN-PID controller to compensate for the nonlinearity of a servomechanism. There are different learning strategies available for updating the weights of RNNs. All of these techniques are based on the gradient descent algorithm. In this research project the Real-Time Recurrent Learning (RTRL) technique will be applied for updating the weights. Numerical simulation will be used to validate the proposed algorithms.College of EngineeringMultidisciplinary ProgramsMaster of Science in Mechatronics Engineering (MSMTR)Dhaouadi, Rached2011-03-10T12:43:55Z2011-03-10T12:43:55Z2005-06info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfapplication/pdfapplication/pdf35.232-2005.01http://hdl.handle.net/11073/100en_USoai:repository.aus.edu:11073/1002025-11-11T07:05:36Z
spellingShingle Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural Networks
Jafari, Reza
Nonlinear control theory
PID controllers
Mechatronics
Feedforward neural networks
Recurrent neural networks
status_str publishedVersion
title Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural Networks
title_full Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural Networks
title_fullStr Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural Networks
title_full_unstemmed Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural Networks
title_short Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural Networks
title_sort Adaptive PID Controller for a Non Linear Pendulum System Using Recurrent Neural Networks
topic Nonlinear control theory
PID controllers
Mechatronics
Feedforward neural networks
Recurrent neural networks
url http://hdl.handle.net/11073/100