Mission Control of Autonomous Underwater Vehicle Using Computational Intelligence, M.Sc. Thesis Sharif University of Technology ; Khayyat, Amir Ali Akbar (Supervisor) ; Ghaemi Osgouie, Kambiz (Co-Advisor)
Abstract
This thesis describes different neural networks models and an approximation based neural network controller for autonomous underwater vehicles (AUVs). The online multilayer perceptron neural networks (OMLPNN) have been designed to perform modeling of AUVs of which the dynamics are highly nonlinear and time varying. The online recurrent multilayer perceptron neural networks (ORMLPNN) have been additionally designed to generate a memory to pervious states and increase the performance of the modeling. The designed OMLPNN and ORMLPNN with the use of backpropagation learning algorithm have advantages and robustness to model the highly nonlinear functions. The proposed neural networks architecture...
Cataloging briefMission Control of Autonomous Underwater Vehicle Using Computational Intelligence, M.Sc. Thesis Sharif University of Technology ; Khayyat, Amir Ali Akbar (Supervisor) ; Ghaemi Osgouie, Kambiz (Co-Advisor)
Abstract
This thesis describes different neural networks models and an approximation based neural network controller for autonomous underwater vehicles (AUVs). The online multilayer perceptron neural networks (OMLPNN) have been designed to perform modeling of AUVs of which the dynamics are highly nonlinear and time varying. The online recurrent multilayer perceptron neural networks (ORMLPNN) have been additionally designed to generate a memory to pervious states and increase the performance of the modeling. The designed OMLPNN and ORMLPNN with the use of backpropagation learning algorithm have advantages and robustness to model the highly nonlinear functions. The proposed neural networks architecture...
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