Underactuated nonlinear adaptive control approach using U-model for multivariable underwater glider control parameters

Underwater glider platform represents the maturing technology with a large cost saving over current underwater sampling process. It can survey and monitor the sea environment cost-effective manner combining survey capabilities, simultaneous water sampling and environmental data gathering capacities....

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Bibliographic Details
Main Authors: Hussain, N.A.A., Ali, S.S.A., Saad, M.N.M., Nordin, N.
Format: Article
Published: Institute of Electrical and Electronics Engineers Inc. 2017
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018337181&doi=10.1109%2fUSYS.2016.7893947&partnerID=40&md5=1359de55efbed205e99b1fe04a425832
http://eprints.utp.edu.my/20101/
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Institution: Universiti Teknologi Petronas
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Summary:Underwater glider platform represents the maturing technology with a large cost saving over current underwater sampling process. It can survey and monitor the sea environment cost-effective manner combining survey capabilities, simultaneous water sampling and environmental data gathering capacities. It can perform a wide range of fully automated monitoring data measurement over an extended period of time. This paper will focus on the design of multivariable underactuated nonlinear adaptive control using U-model methodologies. Underwater glider control, modelling and identification approach was reviewed in order to formulate the design, development and control approach of underwater glider development using multivariable adaptive U-model nonlinear control approach. U-model methodology simplifies the control synthesis with the influence of the uncertainties and external disturbances by selecting appropriate control structures. Most of the autonomous underwater vehicle (AUV) neglected the coupling effect of the dynamics during process modelling while U-model enables to include the coupling effect using the inverse Jacobian matrix. Thus contributes towards the underactuated nonlinear adaptive control development and process modelling. © 2016 IEEE.