Multivariable Neurofuzzy Control of an Autonomous Underwater Vehicle

Authors:
Paul J. Craven;Robert Sutton;Roland S. Burns
Affiliations:
Plymouth Industrial Systems and Control Engineering Group, University of Plymouth, Drake Circus, Plymouth, Devon PL4 8AA, UK;(Correspd.) Plymouth Industrial Systems and Control Engineering Group, University of Plymouth, Drake Circus, Plymouth, Devon PL4 8AA, UK;Plymouth Industrial Systems and Control Engineering Group, University of Plymouth, Drake Circus, Plymouth, Devon PL4 8AA, UK
Venue:
Integrated Computer-Aided Engineering
Year:
1999

Citing 2
Cited 1

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Abstract

This paper discusses the application of a novel multivariable control technique to the problem of autonomous underwater vehicle (AUV) autopilot design. Based on an adaptive neural network structure a multivariable Sugeno style fuzzy inference system is tuned to produce a course-changing and roll minimizing autopilot. Simulation results, performed using a full non-linear six degree of freedom model, illustrate the effectiveness of this new approach when compared to a more traditional control approach which makes no provision for the inherent cross coupling between AUV yaw and roll channels.