Abstract
This paper presents an on-line self-adaptive neuro-fuzzy control that serves as a better alternative control scheme in controlling Autonomous Underwater Vehicles (AUVs) in an uncertain and unstructured environment. The proposed self-adaptive neuro-fuzzy controller is a five-layer feedforward neural network that implements fuzzy basis function (FBF) expansions and is capable of self-constructing and self-restructuring its internal node connectivity and learning the parameters of each node based on incoming training data. Computer simulations have been conducted to validate the performance of the proposed neuro-fuzzy controller and an experimental verification has been scheduled to verify it on ODIN, an autonomous underwater vehicle developed at the University of Hawaii.
Original language | English |
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Pages | 130-135 |
Number of pages | 6 |
Publication status | Published - 1999 |
Event | 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'99): Human and Environment Friendly Robots whith High Intelligence and Emotional Quotients' - Kyongju, South Korea Duration: 1999 Oct 17 → 1999 Oct 21 |
Other
Other | 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'99): Human and Environment Friendly Robots whith High Intelligence and Emotional Quotients' |
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City | Kyongju, South Korea |
Period | 99-10-17 → 99-10-21 |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Software
- Computer Vision and Pattern Recognition
- Computer Science Applications