M. Parsons, A. C. Chubb, Yusong Cao, A. Stefanopoulou
{"title":"An initial assessment of fuzzy logic vessel path control","authors":"M. Parsons, A. C. Chubb, Yusong Cao, A. Stefanopoulou","doi":"10.1109/AUV.1994.518629","DOIUrl":null,"url":null,"abstract":"A fuzzy logic controller for ship path control in restricted waters is developed and evaluated. The controller uses inputs of heading, yaw rate, and lateral offset from the nominal track. A Kalman filter is used to produce the input state variables from noisy measurements. The controller produces a commanded rudder angle. Input variable fuzzification, fuzzy associative memory rules, and output set defuzzification are described. The controller is benchmarked against a conventional linear quadratic Gaussian (LQG) optimal controller and Kalman filter control systems. An initial startup transient and regulator control performance with an external hydrodynamic disturbance are evaluated. The fuzzy controller yields competitive performance.","PeriodicalId":231222,"journal":{"name":"Proceedings of IEEE Symposium on Autonomous Underwater Vehicle Technology (AUV'94)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of IEEE Symposium on Autonomous Underwater Vehicle Technology (AUV'94)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AUV.1994.518629","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
A fuzzy logic controller for ship path control in restricted waters is developed and evaluated. The controller uses inputs of heading, yaw rate, and lateral offset from the nominal track. A Kalman filter is used to produce the input state variables from noisy measurements. The controller produces a commanded rudder angle. Input variable fuzzification, fuzzy associative memory rules, and output set defuzzification are described. The controller is benchmarked against a conventional linear quadratic Gaussian (LQG) optimal controller and Kalman filter control systems. An initial startup transient and regulator control performance with an external hydrodynamic disturbance are evaluated. The fuzzy controller yields competitive performance.
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