PSO approach for a controller based-on backstepping method in stabilizing an underactuated X4-AUV

The autonomous underwater vehicle (AUV) mostly has fewer control inputs than the degree of freedoms (DOFs) in motion and be classified into underactuated system. It is a difficult task to stabilize that system because of the highly nonlinear dynamic and model uncertainties, therefore it is usually r...

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Main Authors: Nurfadzillah, Harun, Zainah, Md. Zain
Format: Conference or Workshop Item
Language:English
Published: 2017
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/21225/
http://umpir.ump.edu.my/id/eprint/21225/1/16.%20Pso%20approach%20for%20a%20controller%20based-on%20backstepping%20method%20in%20stabilizing%20an%20underactuated%20x4-auv.pdf
id ump-21225
recordtype eprints
spelling ump-212252019-10-09T06:29:19Z http://umpir.ump.edu.my/id/eprint/21225/ PSO approach for a controller based-on backstepping method in stabilizing an underactuated X4-AUV Nurfadzillah, Harun Zainah, Md. Zain QA75 Electronic computers. Computer science The autonomous underwater vehicle (AUV) mostly has fewer control inputs than the degree of freedoms (DOFs) in motion and be classified into underactuated system. It is a difficult task to stabilize that system because of the highly nonlinear dynamic and model uncertainties, therefore it is usually required nonlinear control method to control this type of system. Conventionally, to control the system, parameters for the controller are selected by the trial-and-error method or manually chosen. It is challenging to get satisfactory responses because manual tuning is not an easy task and consuming much time, especially involve many parameters. It is necessary to select proper parameters because an improper selection of the parameters may jeopardize the system stability and leads to inappropriate responses. Thus, an optimization technique is required in selecting the optimal parameter for the controller. In this paper, the controller based on backstepping method is required for an underactuated X4-AUV system. Three types of controller based on backstepping are designed ; standard backstepping, PID backstepping and integral backstepping. Twelve optimal parameter values are generated for each controller using particle swarm optimization (PSO). All these three controllers show an improvement in term of settling time, and it has rapid responses compare than a controller with manual tuning parameters. The effectiveness of the controllers is verified in a computer simulation using MATLAB software. 2017 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/21225/1/16.%20Pso%20approach%20for%20a%20controller%20based-on%20backstepping%20method%20in%20stabilizing%20an%20underactuated%20x4-auv.pdf Nurfadzillah, Harun and Zainah, Md. Zain (2017) PSO approach for a controller based-on backstepping method in stabilizing an underactuated X4-AUV. In: 2017 IEEE 7th International Conference on Underwater System Technology: Theory and Applications (USYS’17), 18-20 Disember 2017 , Kuala Lumpur. pp. 1-8..
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Nurfadzillah, Harun
Zainah, Md. Zain
PSO approach for a controller based-on backstepping method in stabilizing an underactuated X4-AUV
description The autonomous underwater vehicle (AUV) mostly has fewer control inputs than the degree of freedoms (DOFs) in motion and be classified into underactuated system. It is a difficult task to stabilize that system because of the highly nonlinear dynamic and model uncertainties, therefore it is usually required nonlinear control method to control this type of system. Conventionally, to control the system, parameters for the controller are selected by the trial-and-error method or manually chosen. It is challenging to get satisfactory responses because manual tuning is not an easy task and consuming much time, especially involve many parameters. It is necessary to select proper parameters because an improper selection of the parameters may jeopardize the system stability and leads to inappropriate responses. Thus, an optimization technique is required in selecting the optimal parameter for the controller. In this paper, the controller based on backstepping method is required for an underactuated X4-AUV system. Three types of controller based on backstepping are designed ; standard backstepping, PID backstepping and integral backstepping. Twelve optimal parameter values are generated for each controller using particle swarm optimization (PSO). All these three controllers show an improvement in term of settling time, and it has rapid responses compare than a controller with manual tuning parameters. The effectiveness of the controllers is verified in a computer simulation using MATLAB software.
format Conference or Workshop Item
author Nurfadzillah, Harun
Zainah, Md. Zain
author_facet Nurfadzillah, Harun
Zainah, Md. Zain
author_sort Nurfadzillah, Harun
title PSO approach for a controller based-on backstepping method in stabilizing an underactuated X4-AUV
title_short PSO approach for a controller based-on backstepping method in stabilizing an underactuated X4-AUV
title_full PSO approach for a controller based-on backstepping method in stabilizing an underactuated X4-AUV
title_fullStr PSO approach for a controller based-on backstepping method in stabilizing an underactuated X4-AUV
title_full_unstemmed PSO approach for a controller based-on backstepping method in stabilizing an underactuated X4-AUV
title_sort pso approach for a controller based-on backstepping method in stabilizing an underactuated x4-auv
publishDate 2017
url http://umpir.ump.edu.my/id/eprint/21225/
http://umpir.ump.edu.my/id/eprint/21225/1/16.%20Pso%20approach%20for%20a%20controller%20based-on%20backstepping%20method%20in%20stabilizing%20an%20underactuated%20x4-auv.pdf
first_indexed 2023-09-18T22:31:03Z
last_indexed 2023-09-18T22:31:03Z
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