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Adaptive trajectory control for the twin rotor MIMO system using artificial neural networks

International Conference on Applications and Design in Mechanical Engineering 2012 (ICADME 2012) organized by School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), 27th - 28th Februari 2012 at Bayview Beach Resort, Penang, Malaysia.

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Bibliographic Details
Main Authors: B. G. D., Achintha Madhusanka, W. R., de Mel
Other Authors: achintha121@yahoo.com
Format: Working Paper
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2012
Subjects:
Dynamic modelling
Neural networks
Twin-rotor system
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/19504
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spelling my.unimap-195042012-05-31T14:09:55Z Adaptive trajectory control for the twin rotor MIMO system using artificial neural networks B. G. D., Achintha Madhusanka W. R., de Mel achintha121@yahoo.com wrmel@ou.ac.lk Dynamic modelling Neural networks Twin-rotor system International Conference on Applications and Design in Mechanical Engineering 2012 (ICADME 2012) organized by School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), 27th - 28th Februari 2012 at Bayview Beach Resort, Penang, Malaysia. This paper investigates the development of an adaptive trajectory dynamic non linear model inversion control law for a twin rotor multi-input multi-output system (TRMS) utilizing artificial neural networks. The behaviour of the TRMS in certain aspects resembles that of a helicopter. A highly non linear one degree freedom model of the TRMS is considered in this study and a non linear inverse model is developed for the pitch channel. In the absence of the model inversion errors, an artificial neural network (ANN) model in place of a proportional-integral-derivative (PID) controller is used to enhance the tracking performance of the system. The neural network model is developed using backpropagation algorithm with Levenberg-Marquardt (LM) training method. The responses between the reference signals and empirical based models of the TRMS to validate the accuracy of the models. Simulation results under MATLAB/Simulink prove the improvement of response and superiority of simplified neural network controller. 2012-05-31T14:09:55Z 2012-05-31T14:09:55Z 2012-02-27 Working Paper http://hdl.handle.net/123456789/19504 en Proceedings of the International Conference on Applications and Design in Mechanical Engineering 2012 (ICADME 2012) Universiti Malaysia Perlis (UniMAP) Pusat Pengajian Kejuruteraan Mekatronik
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 Dynamic modelling
Neural networks
Twin-rotor system
spellingShingle Dynamic modelling
Neural networks
Twin-rotor system
B. G. D., Achintha Madhusanka
W. R., de Mel
Adaptive trajectory control for the twin rotor MIMO system using artificial neural networks
description International Conference on Applications and Design in Mechanical Engineering 2012 (ICADME 2012) organized by School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), 27th - 28th Februari 2012 at Bayview Beach Resort, Penang, Malaysia.
author2 achintha121@yahoo.com
author_facet achintha121@yahoo.com
B. G. D., Achintha Madhusanka
W. R., de Mel
format Working Paper
author B. G. D., Achintha Madhusanka
W. R., de Mel
author_sort B. G. D., Achintha Madhusanka
title Adaptive trajectory control for the twin rotor MIMO system using artificial neural networks
title_short Adaptive trajectory control for the twin rotor MIMO system using artificial neural networks
title_full Adaptive trajectory control for the twin rotor MIMO system using artificial neural networks
title_fullStr Adaptive trajectory control for the twin rotor MIMO system using artificial neural networks
title_full_unstemmed Adaptive trajectory control for the twin rotor MIMO system using artificial neural networks
title_sort adaptive trajectory control for the twin rotor mimo system using artificial neural networks
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2012
url http://dspace.unimap.edu.my/xmlui/handle/123456789/19504
_version_ 1643792815391506432
score 13.214268

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