Automatic steering of ships using neural networks

Unar, M.A. and Murray-Smith, D.J. (1999) Automatic steering of ships using neural networks. Journal of Adaptive Control and Signal Processing, 13(4), pp. 203-218. (doi: 10.1002/(SICI)1099-1115(199906)13:4<203::AID-ACS544>3.0.CO;2-T)

Abstract

Ship steering control system design presents challenges because the dynamic properties of the vessel itself vary significantly. The use of an artificial neural network as a controller which incorporates the properties of a series of conventional controllers designed for different operating conditions could provide an alternative to adaptive control or gain scheduling in this application. Local model network methods could also provide a basis for efficient modelling of the vessel over a range of operating conditions. The paper describes an investigation of radial basis function networks for ship steering control and of local model networks for represention of ship dynamics. performance is demonstrated by a series of simulation studies.

• Item Type: Articles
• Keywords: ship steering control, ship modelling, radial basis function network, local model network
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Murray-Smith, Professor David
• Authors: Unar, M.A., and Murray-Smith, D.J.
• Subjects: Q Science > QA Mathematics > QA76 Computer software; T Technology > TJ Mechanical engineering and machinery; T Technology > TK Electrical engineering. Electronics Nuclear engineering; V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy
• Journal Name: Journal of Adaptive Control and Signal Processing
• ISSN: 0890-6327
• ISSN (Online): 1099-1115
• Published Online: 02 July 1999