Fuzzy Yaw Autopilots for Unmanned Underwater Vehicles Tuned Using Artificial Neural Networks
This paper describes the application of neuro-fuzzy techniques in the design of autopilots for controlling the yaw dynamics of an unmanned underwater vehicle. Autopilots are designed using an adaptive-network-based fuzzy inference system (ANFIS), a simulated annealing tuning methodology, and a fixed fuzzy rule-based approach. To describe the yaw dynamic characteristics of an unmanned underwater vehicle a realistic simulation model is employed. Results are presented which demonstrate the superiority of the ANFIS approach. It is concluded that the approach offers a viable alternative method for designing such autopilots.
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Document Type: Miscellaneous
Publication date: 01 September 1997
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- Underwater Technology is the peer-reviewed international journal of the Society for Underwater Technology. The objectives of the journal are to inform and acquaint the Society's members and other readers with current views and new developments in the broad areas of underwater technology, ocean science and offshore engineering.
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