Linear and nonlinear system identification techniques for modelling of a remotely operated underwater vehicle Online publication date: Tue, 15-Sep-2015
by S.M. Ahmad
International Journal of Modelling, Identification and Control (IJMIC), Vol. 24, No. 1, 2015
Abstract: As opposed to classical mathematical-based modelling approach, this paper reports a black-box system identification technique for characterising the dynamics of a remotely operated vehicle (ROV). A linear system identification technique is employed to model the vehicle dynamics. However, use is also made of advance neural networks-based nonlinear system identification approach to model rudder-depth channel nonlinear behaviour. Different model validity tests are also employed to instil confidence in the identified linear and nonlinear ROV dynamic models. High fidelity models obtained for the multi-degree-of-freedom vehicle are of immense importance for developing ROV simulators, pilot training and autopilot design.
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