Neural network controller design for position control system improvement

This project focused on development of precise position control with a DC motor as an actuator using neural network controller. Neural network controller develop is proposed to overcome the problem of conventional controller weaknesses. Neural network controller is implemented using backpropagati...

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Main Author:	Abdullah, Mohamad Syah Rizal
Format:	Thesis
Language:	English English English
Published:	2013
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://eprints.uthm.edu.my/6671/1/24p%20MOHAMAD%20SYAH%20RIZAL%20ABDULLAH.pdf http://eprints.uthm.edu.my/6671/2/MOHAMAD%20SYAH%20RIZAL%20ABDULLAH%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/6671/3/MOHAMAD%20SYAH%20RIZAL%20ABDULLAH%20WATERMARK.pdf
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id	my-uthm-ep.6671
record_format	uketd_dc
spelling	my-uthm-ep.66712022-03-14T01:45:20Z Neural network controller design for position control system improvement 2013-06 Abdullah, Mohamad Syah Rizal TJ Mechanical engineering and machinery TJ212-225 Control engineering systems. Automatic machinery (General) This project focused on development of precise position control with a DC motor as an actuator using neural network controller. Neural network controller develop is proposed to overcome the problem of conventional controller weaknesses. Neural network controller is implemented using backpropagation training algorithm. Neural network has ability to map unknown relationship input/output system and also nonlinear system. To have knowledge about the system, the neural network is trained using existing controller on the position control system, in this case PID controller. On the training process, neural network controller and PID controller are having same inputs, which are errors. After that, the outputs are compared and the delta of them will used to adjust the network weight until the delta value in the acceptance level. Then, neural network controller is set convergence. At this time, neural network controller ready use to replace PID controller to control the system. To interface between computer where neural network controller is embedded with the DC motor as a position controller system actuator are done using RAPCON platform. Based on the experimental results, show that neural network controller has better performance with the rise time ( ) is 0.02s, the peak time ( ) is 0.05s, settling time ( ) is 0.05s, and percentage overshoot ( ) is 2.0%. 2013-06 Thesis http://eprints.uthm.edu.my/6671/ http://eprints.uthm.edu.my/6671/1/24p%20MOHAMAD%20SYAH%20RIZAL%20ABDULLAH.pdf text en public http://eprints.uthm.edu.my/6671/2/MOHAMAD%20SYAH%20RIZAL%20ABDULLAH%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/6671/3/MOHAMAD%20SYAH%20RIZAL%20ABDULLAH%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Malaysia Fakulti Kejuruteraan Elektrik dan Elektronik
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	TJ Mechanical engineering and machinery TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery TJ Mechanical engineering and machinery Abdullah, Mohamad Syah Rizal Neural network controller design for position control system improvement
description	This project focused on development of precise position control with a DC motor as an actuator using neural network controller. Neural network controller develop is proposed to overcome the problem of conventional controller weaknesses. Neural network controller is implemented using backpropagation training algorithm. Neural network has ability to map unknown relationship input/output system and also nonlinear system. To have knowledge about the system, the neural network is trained using existing controller on the position control system, in this case PID controller. On the training process, neural network controller and PID controller are having same inputs, which are errors. After that, the outputs are compared and the delta of them will used to adjust the network weight until the delta value in the acceptance level. Then, neural network controller is set convergence. At this time, neural network controller ready use to replace PID controller to control the system. To interface between computer where neural network controller is embedded with the DC motor as a position controller system actuator are done using RAPCON platform. Based on the experimental results, show that neural network controller has better performance with the rise time ( ) is 0.02s, the peak time ( ) is 0.05s, settling time ( ) is 0.05s, and percentage overshoot ( ) is 2.0%.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Abdullah, Mohamad Syah Rizal
author_facet	Abdullah, Mohamad Syah Rizal
author_sort	Abdullah, Mohamad Syah Rizal
title	Neural network controller design for position control system improvement
title_short	Neural network controller design for position control system improvement
title_full	Neural network controller design for position control system improvement
title_fullStr	Neural network controller design for position control system improvement
title_full_unstemmed	Neural network controller design for position control system improvement
title_sort	neural network controller design for position control system improvement
granting_institution	Universiti Tun Hussein Malaysia
granting_department	Fakulti Kejuruteraan Elektrik dan Elektronik
publishDate	2013
url	http://eprints.uthm.edu.my/6671/1/24p%20MOHAMAD%20SYAH%20RIZAL%20ABDULLAH.pdf http://eprints.uthm.edu.my/6671/2/MOHAMAD%20SYAH%20RIZAL%20ABDULLAH%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/6671/3/MOHAMAD%20SYAH%20RIZAL%20ABDULLAH%20WATERMARK.pdf
_version_	1747831081639346176

Neural network controller design for position control system improvement

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