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An intelligent guidance and control system for ship obstacle avoidance

An intelligent guidance and control system for ship obstacle avoidance
An intelligent guidance and control system for ship obstacle avoidance
An intelligent guidance and control system using a neurofuzzy network multistep ahead predictor model is introduced and applied to ship obstacle avoidance, which uses only observed input/output data generated by on board and external sensors, and a data fusion algorithm to generate the desired waypoints. A simple and effective waypoint guidance scheme based on line-of-sight is derived for a data based ship model. A neurofuzzy network predictor, based on using rudder deflection angle for the control of ship heading angle, is utilised on the simulation of ESSO 190000dwt tanker model to demonstrate the effectiveness of the system. The approach is generic and extendable to aircraft and missile control and guidance problems where the vehicle dynamics change significantly during flight in a manner dependent upon operational use, the only requirement for implementation being observed data to construct sensor and vehicle models.
135-40
Harris, C. J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Hong, X.
b8f251c3-e142-4555-a54c-c504de966b03
Wilson, P.A
bd99bfcc-424f-4942-9e39-f255f4daa6bf
Harris, C. J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Hong, X.
b8f251c3-e142-4555-a54c-c504de966b03
Wilson, P.A
bd99bfcc-424f-4942-9e39-f255f4daa6bf

Harris, C. J., Hong, X. and Wilson, P.A (1999) An intelligent guidance and control system for ship obstacle avoidance. pp. 135-40 .

Record type: Conference or Workshop Item (Other)

Abstract

An intelligent guidance and control system using a neurofuzzy network multistep ahead predictor model is introduced and applied to ship obstacle avoidance, which uses only observed input/output data generated by on board and external sensors, and a data fusion algorithm to generate the desired waypoints. A simple and effective waypoint guidance scheme based on line-of-sight is derived for a data based ship model. A neurofuzzy network predictor, based on using rudder deflection angle for the control of ship heading angle, is utilised on the simulation of ESSO 190000dwt tanker model to demonstrate the effectiveness of the system. The approach is generic and extendable to aircraft and missile control and guidance problems where the vehicle dynamics change significantly during flight in a manner dependent upon operational use, the only requirement for implementation being observed data to construct sensor and vehicle models.

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More information

Published date: 1999
Additional Information: Organisation: International ICSC Conference on Computational Intelligence Methods and Applications (CIMA'99), Fuzzy Logic And applications (ISFL'99), Rochester, USA
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 250662
URI: http://eprints.soton.ac.uk/id/eprint/250662
PURE UUID: 836c87d6-f136-4e31-a899-6391018bc66b

Catalogue record

Date deposited: 29 Mar 2000
Last modified: 16 Jul 2019 23:11

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Contributors

Author: C. J. Harris
Author: X. Hong
Author: P.A Wilson

University divisions

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