On-line self-organizing neuro-fuzzy control for autonomous underwater vehicles

Jeen Shing Wang, C. S.George Lee, Junku Yuh

Research output: Contribution to journalConference articlepeer-review

13 Citations (Scopus)


Controlling Autonomous Underwater Vehicles (AUVs) in an uncertain and unstructured environment presents many challenging control problems. Model-based control strategies have been used with limited success. This paper presents an on-line self-organizing neuro-fuzzy control that serves as a better alternative control scheme in controlling AUVs. The proposed self-organizing neuro-fuzzy controller is a six-layer feedforward neural network that 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 languageEnglish
Pages (from-to)2416-2421
Number of pages6
JournalProceedings - IEEE International Conference on Robotics and Automation
Publication statusPublished - 1999 Jan 1
EventProceedings of the 1999 IEEE International Conference on Robotics and Automation, ICRA99 - Detroit, MI, USA
Duration: 1999 May 101999 May 15

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering


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