Multivariable Neurofuzzy Control of an Autonomous Underwater Vehicle

Article type: Research Article

Authors: Craven, Paul J. | Sutton, Robert | Burns, Roland S.^{; *}

Affiliations: Plymouth Industrial Systems and Control Engineering Group, University of Plymouth, Drake Circus, Plymouth, Devon PL4 8AA, UK

Correspondence: [*] Correspondence to: Dr. Robert Sutton.

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.

DOI: 10.3233/ICA-1999-6402

Journal: Integrated Computer-Aided Engineering, vol. 6, no. 4, pp. 275-288, 1999