Neural-tuned PID controller for Point-to-point (PTP) positioning system: model reference approach

Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia.

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Bibliographic Details
Main Authors:	Wahyudi, Wali Ahmad, Min Htut, Myo
Other Authors:	wahyudi@iiu.edu.my
Format:	Working Paper
Language:	English
Published:	Universiti Malaysia Perlis 2009
Subjects:	Point-to-Point (PTP) Motion control systems Automatic control PID controllers > Design and construction PID controllers Motion control
Online Access:	http://dspace.unimap.edu.my/xmlui/handle/123456789/7283
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Institution:	Universiti Malaysia Perlis
Language:	English

id	my.unimap-7283
record_format	dspace
spelling	my.unimap-72832010-01-21T01:44:05Z Neural-tuned PID controller for Point-to-point (PTP) positioning system: model reference approach Wahyudi, Wali Ahmad Min Htut, Myo wahyudi@iiu.edu.my Point-to-Point (PTP) Motion control systems Automatic control PID controllers -- Design and construction PID controllers Motion control Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia. Point-to-Point (PTP) motion control systems play an important role in industrial engineering applications such as advanced manufacturing systems, semiconductor manufacturing systems and robot systems. Until now, Proportional-Integral-Derivative (PID) controllers are still the most popular controller used in industrial control systems including PTP motion control systems due to their simplicity and also satisfactory performances. However, since the PID controller is developed based on the linear control theory, the controller gives inconsistent performance for different condition due to system nonlinearities. In order to overcome this problem, Neural-tuned PID control using Model Reference Adaptive Control (MRAC) is proposed. By using Extended Minimal Resource Allocation Algorithm (EMRAN) to train the Radial Basis Funciton (RBF) Network, the PID controller can learn, adapt and change its parameters based on the condition of the controlled-object in real-time. The effectiveness of the proposed method is evaluated experimentally in real time using an experimental rotary positioning system. The experimental results show that the proposed system is better than classical PID controller in terms of not only positioning performance but also robustness to inertia variations. 2009-11-13T02:36:23Z 2009-11-13T02:36:23Z 2009-10-11 Working Paper http://hdl.handle.net/123456789/7283 en Proceedings of the International Conference on Man-Machine Systems (ICoMMS 2009) Universiti Malaysia Perlis
institution	Universiti Malaysia Perlis
building	UniMAP Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Perlis
content_source	UniMAP Library Digital Repository
url_provider	http://dspace.unimap.edu.my/
language	English
topic	Point-to-Point (PTP) Motion control systems Automatic control PID controllers -- Design and construction PID controllers Motion control
spellingShingle	Point-to-Point (PTP) Motion control systems Automatic control PID controllers -- Design and construction PID controllers Motion control Wahyudi, Wali Ahmad Min Htut, Myo Neural-tuned PID controller for Point-to-point (PTP) positioning system: model reference approach
description	Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia.
author2	wahyudi@iiu.edu.my
author_facet	wahyudi@iiu.edu.my Wahyudi, Wali Ahmad Min Htut, Myo
format	Working Paper
author	Wahyudi, Wali Ahmad Min Htut, Myo
author_sort	Wahyudi, Wali Ahmad
title	Neural-tuned PID controller for Point-to-point (PTP) positioning system: model reference approach
title_short	Neural-tuned PID controller for Point-to-point (PTP) positioning system: model reference approach
title_full	Neural-tuned PID controller for Point-to-point (PTP) positioning system: model reference approach
title_fullStr	Neural-tuned PID controller for Point-to-point (PTP) positioning system: model reference approach
title_full_unstemmed	Neural-tuned PID controller for Point-to-point (PTP) positioning system: model reference approach
title_sort	neural-tuned pid controller for point-to-point (ptp) positioning system: model reference approach
publisher	Universiti Malaysia Perlis
publishDate	2009
url	http://dspace.unimap.edu.my/xmlui/handle/123456789/7283
_version_	1643788747800576000

Neural-tuned PID controller for Point-to-point (PTP) positioning system: model reference approach

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