Journal of the Korean Society of Fisheries and Ocean Technology (수산해양기술연구)

The Korean Society of Fisheries and Ocean Technology (한국수산해양기술학회)
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T-S fuzzy PID control based on RCGAs for the automatic steering system of a ship

선박자동조타를 위한 RCGA기반 T-S 퍼지 PID 제어

  • Yu-Soo LEE (Global Customer Operation Experts, Winterthur Gas & Diesel Korea) ;
  • Soon-Kyu HWANG (Energy System R&D Department, DSME) ;
  • Jong-Kap AHN (Training Ship Operation Center, Gyeongsang National University)
  • 이유수 (윈터투어 가스앤디젤 코리아) ;
  • 황순규 (대우조선해양 에너지시스템 연구개발부) ;
  • 안종갑 (경상국립대학교 실습선 운영관리센터)
  • Received : 2023.01.30
  • Accepted : 2023.02.20
  • Published : 2023.02.28
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Abstract

In this study, the second-order Nomoto's nonlinear expansion model was implemented as a Tagaki-Sugeno fuzzy model based on the heading angular velocity to design the automatic steering system of a ship considering nonlinear elements. A Tagaki-Sugeno fuzzy PID controller was designed using the applied fuzzy membership functions from the Tagaki-Sugeno fuzzy model. The linear models and fuzzy membership functions of each operating point of a given nonlinear expansion model were simultaneously tuned using a genetic algorithm. It was confirmed that the implemented Tagaki-Sugeno fuzzy model could accurately describe the given nonlinear expansion model through the Zig-Zag experiment. The optimal parameters of the sub-PID controller for each operating point of the Tagaki-Sugeno fuzzy model were searched using a genetic algorithm. The evaluation function for searching the optimal parameters considered the route extension due to course deviation and the resistance component of the ship by steering. By adding a penalty function to the evaluation function, the performance of the automatic steering system of the ship could be evaluated to track the set course without overshooting when changing the course. It was confirmed that the sub-PID controller for each operating point followed the set course to minimize the evaluation function without overshoot when changing the course. The outputs of the tuned sub-PID controllers were combined in a weighted average method using the membership functions of the Tagaki-Sugeno fuzzy model. The proposed Tagaki-Sugeno fuzzy PID controller was applied to the second-order Nomoto's nonlinear expansion model. As a result of examining the transient response characteristics for the set course change, it was confirmed that the set course tracking was satisfactorily performed.

Keywords

References

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