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Improved S-plane control for underwater vehicles
Proceedings of the 10th World Congress on Intelligent Control and Automation
Year: 2012 | Conference Paper |
Research on control for underwater vehicle is undertaken. S-plane control is verified to be effective in control of underwater vehicles. But there are problems in steady precision and parameter adjustments. In order to obtain higher steady precision, intelligent integral is brought in, and expert S-plane control is presented to tune the parameters on-line based on expert control and S-plane contro...Show More
Fault diagnosis of underwater vehicle with FNN
Proceedings of the 10th World Congress on Intelligent Control and Automation
Year: 2012 | Conference Paper |
Cited by: Papers (7)
Aiming at the character that the uncertainties of the complex system of underwater vehicle (UV) bring to model the system very difficult, a fuzzy neural network (FNN) with least adjustment is proposed to construct the motion model of UV. The adjustment of the dynamic learning rate and weights of FNN is studied. The FNN has the ability not only to approach the whole figure of a function but also to...Show More
Wavelet neural network applied to fault diagnosis of underwater vehicle
Jianguo Wang;Lei Wan;Chunmeng Jiang;Yushan Sun;Bin He;Jiqing Li
Proceedings of the 30th Chinese Control Conference
Year: 2011 | Conference Paper |
Cited by: Papers (2)
To aim at the character that the uncertainties of the complex system of Autonomous Underwater Vehicle (AUV) bring to model the system difficult, a wavelet neural network (WNN) is proposed to construct the motion model of AUV. The adjustment of the scale factor and shift factor of wavelet and weights of WNN is studied. The WNN has the ability not only to approach the whole figure of a function but ...Show More
Fault diagnosis of Underwater Robots based on recurrent neural network
2009 IEEE International Conference on Robotics and Biomimetics (ROBIO)
Year: 2009 | Conference Paper |
Cited by: Papers (3)
Research on thruster fault diagnosis of Underwater Robots (URs) is undertaken to improve its whole system reliability. Based on the BP neural network, a recurrent neural network (RNN) is presented and the network training algorithm is deduced. The RNN is trained by voyage head and yaw turning experiments, and the well trained network is applied to model for the URs. Compared the outputs between mo...Show More
Recurrent neural network applied to fault diagnosis of Underwater Robots
2009 IEEE International Conference on Intelligent Computing and Intelligent Systems
Year: 2009 | Conference Paper |
Cited by: Papers (9)
Study of thruster fault diagnosis of Underwater Robots (URs) is undertaken to improve its whole system reliability. Based on the BP neural network, an improved recurrent neural network (RNN) is proposed and the network training algorithm is deduced. The RNN is trained by voyage head and yaw turning experiments, and the well trained network is applied to model for the URs. Compared the model's outp...Show More
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