Abstract
In this article the use of neural networks in models for underwater vehicles is discussed. Rather than using a neural network parallel to the known model to account for unmodeled phenomena in a model wide fashion, knowledge regarding the various parts of the model is used to apply neural networks for those parts of the model that are most uncertain. As an example, the damping of an underwater vehicle is identified using neural networks. The performance of the neural network based model is demonstrated for an AUV that changes its physical characteristics during a simulated intervention operation.
Original language | English |
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Pages (from-to) | 263-268 |
Number of pages | 6 |
Journal | IFAC Proceedings Volumes (IFAC-PapersOnline) |
Volume | 37 |
Issue number | 10 |
DOIs | |
Publication status | Published - 2004 |
Externally published | Yes |
Event | 2004 IFAC Conference on Computer Applications in Marine Systems, CAMS 2004 - Ancona, Italy Duration: 7 Jul 2004 → 9 Jul 2004 |
Keywords
- Autonomous vehicles
- Back propagation
- Marine systems. neural networks
- Nonlinear systems
- System identification
- Time-varying systems