Tuning fuzzy ship autopilots using artificial neural networks-Reference-Cited by-同舟云学术

Tuning fuzzy ship autopilots using artificial neural networks

Published:1997-04 Issue:2 Volume:19 Page:94-106
ISSN:0142-3312
Container-title:Transactions of the Institute of Measurement and Control
language:en
Short-container-title:Transactions of the Institute of Measurement and Control

Author:

Sutton R.¹,Roberts G.N.²,Taylor S.D.H.¹

Affiliation:

1. Marine Dynamics Research Group, Marine Technology Division, Institute of Marine Studies, University of Plymouth, Plymouth PL4 8AA, UK

2. Faculty of Technology, University of Wales College Newport, Allt-yr-yn Campus, PO Box 180, Newport MP9 5XR, UK

Abstract

This paper is concerned with an investigation into the use of artificial neural networks in the design of fuzzy autopilots for controlling the non-linear yaw dynamics of a modern Royal Navy warship model. Artificial neural networks are used to tune the consequent portion of the fuzzy conditional statements which constitute the fuzzy autopilots and comparisons are made between several training algorithms and two different network structures. Results are presented to show the viability of such an approach and that effective designs can be produced.

Publisher

SAGE Publications

Subject

Instrumentation

Link

http://journals.sagepub.com/doi/pdf/10.1177/014233129701900204

Reference27 articles.

1. Neuronlike adaptive elements that can solve difficult learning control problems

2. Neural Computing: An Introduction

3. Learning and tuning fuzzy logic controllers through reinforcements

4. Artificial Neural Networks

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