TY  - JOUR
PB  - National Institute of Science Communication and Policy Research
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85037054662&partnerID=40&md5=1429d8df3fdfc565e0dd86988a0f7666
Y1  - 2017///
A1  - Hussain, N.A.A.
A1  - Ali, S.S.A.
A1  - Saad, M.N.M.
A1  - Ovinis, M.
A1  - Nordin, N.
A1  - Adil, S.H.
ID  - scholars8086
TI  - Underactuated nonlinear adaptive control approach using U-model incorporated with RBFNN for multivariable underwater glider control parameters
SN  - 25826506
IS  - 12
SP  - 2482
N1  - cited By 2
JF  - Indian Journal of Geo-Marine Sciences
VL  - 46
N2  - 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. U-model incorporated with RBFNN enhance the adaptive nonlinear control synthesis. Thus contributes towards the underactuated nonlinear adaptive control development and process modelling. © 2017, National Institute of Science Communication and Information Resources (NISCAIR). All rights reserved.
AV  - none
EP  - 2492
KW  - autonomous underwater vehicle; control system; design; monitoring; multivariate analysis; nonlinearity
ER  -