Title: Linear and nonlinear system identification techniques for modelling of a remotely operated underwater vehicle
Authors: S.M. Ahmad
Addresses: Faculty of Mechanical Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Topi-23640, Swabi, KPK, Pakistan
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.
Keywords: remotely operated underwater vehicles; ROV modelling; linear system identification; neural networks; nonlinear system identification; ROV dynamics; dynamic modelling; remotely operated vehicles; rudder-depth channel nonlinear behaviour.
International Journal of Modelling, Identification and Control, 2015 Vol.24 No.1, pp.75 - 87
Available online: 15 Sep 2015 *Full-text access for editors Access for subscribers Purchase this article Comment on this article