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dc.contributor.authorKia, C.-
dc.contributor.authorArshad, M.R.-
dc.contributor.authorAbdul Hamid, Adom-
dc.contributor.authorWilson, P.A.-
dc.date.accessioned2013-12-23T08:43:00Z-
dc.date.available2013-12-23T08:43:00Z-
dc.date.issued2005-07-30-
dc.identifier.citationKia, C., Arshad, M.R., Adom, A.H., Wilson, P.A. Supervisory fuzzy learning control for underwater target tracking (2005) Proceedings - WEC 05: Fourth World Enformatika Conference, 6, pp. 92-95.en_US
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/30800-
dc.description.abstractThis paper presents recent work on the improvement of the robotics vision based control strategy for underwater pipeline tracking system. The study focuses on developing image processing algorithms and a fuzzy inference system for the analysis of the terrain. The main goal is to implement the supervisory fuzzy learning control technique to reduce the errors on navigation decision due to the pipeline occlusion problem. The system developed is capable of interpreting underwater images containing occluded pipeline, seabed and other unwanted noise. The algorithm proposed in previous work does not explore the cooperation between fuzzy controllers, knowledge and leamt data to improve the outputs for underwater pipeline tracking. Computer simulations and prototype simulations demonstrate the effectiveness of this approach. The system accuracy level has also been discussed.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesWorld Enformatika Conference;4th, 2005-
dc.subjectArtificial intelligenceen_US
dc.subjectAutonomous underwater vehiclesen_US
dc.subjectFuzzy controlen_US
dc.subjectFuzzy controlleren_US
dc.subjectImage processingen_US
dc.subjectPipelinesen_US
dc.titleSupervisory fuzzy learning control for underwater target trackingen_US
dc.typeWorking Paperen_US
dc.publisher.departmentSchool of Mechatronics Engineeringen_US
Appears in Collections:2005
Abdul Hamid Adom, Prof. Dr.

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