A Marine Autopilot With a Fuzzy Controller Computed by a Neural Network
- 10.2991/itids-19.2019.31How to use a DOI?
- marine autopilot, fuzzy controller, neural network
The paper proposes simulation findings for an autopilot IC-2005 on a signal simulator developed by the authors of an intelligent control system to steer a sea vessel. The principle of the intelligent control system operation consists of generating a data vector with values of the yaw angle of the vessel, the rate of the angle change, the rudder displacement values and the rate of angling the rudder blade change during the ship heading. The features of the seaway provided by current wind and wave conditions are defined through spectral analysis. Then the intelligent classifier of the control system selects the optimal pre-trained neural network model of the seaway from a series of them. The fuzzy logic controller settings are computed after that. 120 search patterns for six types of vessels in various navigation conditions were developed using the simulator as a result of modeling. 79 neural networks were trained, and 2518 neural network way models of them were obtained for a representative sample of search patterns. The top settings of neural networks to develop search pattern models of the seaways were identified in response to statistical manipulation. As exemplified by a trawler ship type, computer and simulation methods were carried out that proved the efficiency of the approach proposed to apply to an intelligent sea craft automatic heading control system
- © 2019, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Nelly Sedova AU - Viktor Sedov AU - Ruslan Bazhenov AU - Irina Ledovskikh PY - 2019/05 DA - 2019/05 TI - A Marine Autopilot With a Fuzzy Controller Computed by a Neural Network BT - Proceedings of the 7th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2019) PB - Atlantis Press SP - 171 EP - 176 SN - 1951-6851 UR - https://doi.org/10.2991/itids-19.2019.31 DO - 10.2991/itids-19.2019.31 ID - Sedova2019/05 ER -