Active vortex induced vibration controller and Neuro identification for marine risers

In this work, a vortex induced vibration controller within discrete time has been investigated on marine cylinder pipe risers which represented by using nonlinear neuron identification models namely NARX and NAR. Input-output data have been extracted from the experimental rig of vortex induced vibra...

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Main Authors: Mohammed, Mohammed Jawad, Mat Darus, Intan Zaurah
Format: Article
Language:English
Published: Asian Research Publishing Network 2014
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Online Access:http://eprints.utm.my/id/eprint/51715/1/IntanZaurahMat2014_Activevortexinducedvibrationcontroller.pdf
http://eprints.utm.my/id/eprint/51715/
https://www.researchgate.net/publication/288130308
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spelling my.utm.517152018-08-27T03:24:23Z http://eprints.utm.my/id/eprint/51715/ Active vortex induced vibration controller and Neuro identification for marine risers Mohammed, Mohammed Jawad Mat Darus, Intan Zaurah TJ Mechanical engineering and machinery In this work, a vortex induced vibration controller within discrete time has been investigated on marine cylinder pipe risers which represented by using nonlinear neuron identification models namely NARX and NAR. Input-output data have been extracted from the experimental rig of vortex induced vibration marine riser. A proposed work in this paper is to create the nonlinear system identification model undergoing for vortex induced vibration of marine riser depends on Neural Network which didn’t represented before this time in this application and using PID controller to suppress the vibration. Two nonlinear system identification methods used to represent the models which are: Neural Network based on Nonlinear Auto-Regressive External (Exogenous) Input (NARX) and Neural Network based on Nonlinear Auto-Regressive (NAR). Also, the best model has been chosen based on the lowest value of Mean Square Error (MSE) between actual and predicted response. While, PID controller has been used to suppress the oscillation of pipe cylinder for all models and the comparison of the controller’s performance on each model by tuning the controller parameter (KP, KI and KD) using heuristic method. Finally, the outcomes show that the NARX model performed better than the NAR model to predict the dynamic response of the system. On the other hand, PID controller has been managed to reduce the pipe cylinder fluctuation for all models specially the NARX model. Using particle swarm optimization (PSO) to improve the stability for marine riser on the parameters of PID controller are planned for future work Asian Research Publishing Network 2014 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/51715/1/IntanZaurahMat2014_Activevortexinducedvibrationcontroller.pdf Mohammed, Mohammed Jawad and Mat Darus, Intan Zaurah (2014) Active vortex induced vibration controller and Neuro identification for marine risers. Journal of Theoretical and Applied Information Technology, 70 (1). pp. 153-162. ISSN 1992-8645 https://www.researchgate.net/publication/288130308
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 TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Mohammed, Mohammed Jawad
Mat Darus, Intan Zaurah
Active vortex induced vibration controller and Neuro identification for marine risers
description In this work, a vortex induced vibration controller within discrete time has been investigated on marine cylinder pipe risers which represented by using nonlinear neuron identification models namely NARX and NAR. Input-output data have been extracted from the experimental rig of vortex induced vibration marine riser. A proposed work in this paper is to create the nonlinear system identification model undergoing for vortex induced vibration of marine riser depends on Neural Network which didn’t represented before this time in this application and using PID controller to suppress the vibration. Two nonlinear system identification methods used to represent the models which are: Neural Network based on Nonlinear Auto-Regressive External (Exogenous) Input (NARX) and Neural Network based on Nonlinear Auto-Regressive (NAR). Also, the best model has been chosen based on the lowest value of Mean Square Error (MSE) between actual and predicted response. While, PID controller has been used to suppress the oscillation of pipe cylinder for all models and the comparison of the controller’s performance on each model by tuning the controller parameter (KP, KI and KD) using heuristic method. Finally, the outcomes show that the NARX model performed better than the NAR model to predict the dynamic response of the system. On the other hand, PID controller has been managed to reduce the pipe cylinder fluctuation for all models specially the NARX model. Using particle swarm optimization (PSO) to improve the stability for marine riser on the parameters of PID controller are planned for future work
format Article
author Mohammed, Mohammed Jawad
Mat Darus, Intan Zaurah
author_facet Mohammed, Mohammed Jawad
Mat Darus, Intan Zaurah
author_sort Mohammed, Mohammed Jawad
title Active vortex induced vibration controller and Neuro identification for marine risers
title_short Active vortex induced vibration controller and Neuro identification for marine risers
title_full Active vortex induced vibration controller and Neuro identification for marine risers
title_fullStr Active vortex induced vibration controller and Neuro identification for marine risers
title_full_unstemmed Active vortex induced vibration controller and Neuro identification for marine risers
title_sort active vortex induced vibration controller and neuro identification for marine risers
publisher Asian Research Publishing Network
publishDate 2014
url http://eprints.utm.my/id/eprint/51715/1/IntanZaurahMat2014_Activevortexinducedvibrationcontroller.pdf
http://eprints.utm.my/id/eprint/51715/
https://www.researchgate.net/publication/288130308
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score 13.160551