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Modeling and controller design of an inverted pendulum system using AI approach

This project presents the simulation study of few different control approaches that consist of modern controller and intelligent controller for an inverted pendulum system. Inverted pendulum is a nonlinear and unstable dynamic system, which continually moves toward an uncontrolled state. It consists...

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Main Author: Najafzadeh, Nazila
Format: Thesis
Language:English
Published: 2012
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/32284/5/NazilaNajafzadehMFKE2012.pdf
http://eprints.utm.my/id/eprint/32284/
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spelling my.utm.322842018-05-27T07:44:12Z http://eprints.utm.my/id/eprint/32284/ Modeling and controller design of an inverted pendulum system using AI approach Najafzadeh, Nazila TK Electrical engineering. Electronics Nuclear engineering This project presents the simulation study of few different control approaches that consist of modern controller and intelligent controller for an inverted pendulum system. Inverted pendulum is a nonlinear and unstable dynamic system, which continually moves toward an uncontrolled state. It consists of a cart, driven by a force that can move along a horizontal track, and a pendulum attached to the cart which can rotate freely in the vertical plane parallel to the track. The control problem is to drive the pendulum to its upright position and remains it there as well as maintaining the position of the cart. It involves the derivation of the mathematical modeling that includes the linearization of the model in order to be used with the linear controller. The work follows with designing linear quadric regulator (LQR) as modern controller; fuzzy logic and adaptive neural network fuzzy for the intelligent controller. The simulation of controllers has been done in MATLAB, and their performance is analyzed and compared which is based on common criteria’s of the step response. Overall, LQR controller has the fastest response, whereas adaptive neural network fuzzy controller gives more flexibility in control action 2012-01 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/32284/5/NazilaNajafzadehMFKE2012.pdf Najafzadeh, Nazila (2012) Modeling and controller design of an inverted pendulum system using AI approach. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Najafzadeh, Nazila
Modeling and controller design of an inverted pendulum system using AI approach
description This project presents the simulation study of few different control approaches that consist of modern controller and intelligent controller for an inverted pendulum system. Inverted pendulum is a nonlinear and unstable dynamic system, which continually moves toward an uncontrolled state. It consists of a cart, driven by a force that can move along a horizontal track, and a pendulum attached to the cart which can rotate freely in the vertical plane parallel to the track. The control problem is to drive the pendulum to its upright position and remains it there as well as maintaining the position of the cart. It involves the derivation of the mathematical modeling that includes the linearization of the model in order to be used with the linear controller. The work follows with designing linear quadric regulator (LQR) as modern controller; fuzzy logic and adaptive neural network fuzzy for the intelligent controller. The simulation of controllers has been done in MATLAB, and their performance is analyzed and compared which is based on common criteria’s of the step response. Overall, LQR controller has the fastest response, whereas adaptive neural network fuzzy controller gives more flexibility in control action
format Thesis
author Najafzadeh, Nazila
author_facet Najafzadeh, Nazila
author_sort Najafzadeh, Nazila
title Modeling and controller design of an inverted pendulum system using AI approach
title_short Modeling and controller design of an inverted pendulum system using AI approach
title_full Modeling and controller design of an inverted pendulum system using AI approach
title_fullStr Modeling and controller design of an inverted pendulum system using AI approach
title_full_unstemmed Modeling and controller design of an inverted pendulum system using AI approach
title_sort modeling and controller design of an inverted pendulum system using ai approach
publishDate 2012
url http://eprints.utm.my/id/eprint/32284/5/NazilaNajafzadehMFKE2012.pdf
http://eprints.utm.my/id/eprint/32284/
_version_ 1643648994819178496
score 13.211869

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