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Adaptable Fuzzy Expert System for Ship Lock Control Support

Published online by Cambridge University Press:  03 May 2016

Todor Bačkalić Open the ORCID record for Todor Bačkalić [Opens in a new window] ,
Vladimir Bugarski Open the ORCID record for Vladimir Bugarski [Opens in a new window] ,
Filip Kulić  and
Željko Kanović
Todor Bačkalić*
Affiliation:
(University of Novi Sad, Faculty of Technical Sciences)
Vladimir Bugarski
Affiliation:
(University of Novi Sad, Faculty of Technical Sciences)
Filip Kulić
Affiliation:
(University of Novi Sad, Faculty of Technical Sciences)
Željko Kanović
Affiliation:
(University of Novi Sad, Faculty of Technical Sciences)
*
(E-mail: tosa@uns.ac.rs)
Get access Rights & Permissions [Opens in a new window]

Abstract

A ship lock zone represents a specific area on waterway, and control of the ship lockage process requires a comprehensive approach. This research is a practical application of a Mamdani-type fuzzy inference system and particle swarm optimisation to control this process. It presents an optimisation process that adapts control logic to the desired criteria. The initially proposed Fuzzy Expert System (FES) was developed using suggestions from lockmasters (ship lock operators) with extensive experience. Further optimisation of the membership function parameters of the input variables was performed to achieve better results in the local distribution of ship arrivals. The presented fuzzy logic-based expert system was designed as part of a Programmable Logic Controller (PLC) and Supervisory Control And Data Acquisition (SCADA) system to support decision making and control. The developed fuzzy algorithm is a rare application of artificial intelligence in navigable canals and significantly improves performance of the ship lockage process. This adaptable FES is designed to be used as a support in decision-making processes or for the direct control of ship lock operations.

Keywords

Ship lockVessel trafficFuzzy expert systemOptimisation
Type
Research Article
Information
The Journal of Navigation , Volume 69 , Issue 6 , November 2016 , pp. 1341 - 1356
Copyright
Copyright © The Royal Institute of Navigation 2016 

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