Development of automatic gain-tuning algorithm for heading control using free-running test data
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초록
This study proposes an automatic gain-tuning algorithm for ships. The proposed algorithm is designed to tune the gains of the ship controller automatically, rather than using trial and error. The forward speed and steering models were derived by linearizing and simplifying the 3-degrees of freedom (DOF) nonlinear equation of motion of the ship. The initial control gains were calculated using an error dynamics model constructed by combining the steering and system models of the controller. The maneuvering simulations and sensitivity analysis of the control performance at various control gains were performed for gain-tuning. System identification was conducted based on derived dynamics models and free-running test data. The tests verified that the gain-tuning algorithm corrects the gains more accurately and rapidly than trial and error. In addition, the algorithm reduced overshoot by 85% compared to the initial control gains.
Abstract
This study proposes an automatic gain-tuning algorithm for ships. The proposed algorithm is designed to tune the gains of the ship controller automatically, rather than using trial and error. The forward speed and steering models were derived by linearizing and simplifying the 3-degrees of freedom (DOF) nonlinear equation of motion of the ship. The initial control gains were calculated using an error dynamics model constructed by combining the steering and system models of the controller. The maneuvering simulations and sensitivity analysis of the control performance at various control gains were performed for gain-tuning. System identification was conducted based on derived dynamics models and free-running test data. The tests verified that the gain-tuning algorithm corrects the gains more accurately and rapidly than trial and error. In addition, the algorithm reduced overshoot by 85% compared to the initial control gains.
참고문헌 (25)
- Fossen, T. I., "Nonlinear Modelling and Control of Underwater Vehicles", Doctoral, pp.1991
- Fossen, T. I., "Guidance and Control of Ocean Vehicles" (1994), John Wiley & Sons Inc
- Namkyun Im, "Artificial neural network controller for automatic ship berthing using head-up coordinate system", International Journal of Naval Architecture and Ocean Engineering, 10(3), pp.235~249 (2018), 대한조선학회
- 조현재, "로봇운영체제를 이용한 보트의 자율운항 알고리즘 개발", 대한조선학회 논문집, 58(2), pp.121~128 (2021), 대한조선학회[DOI]
- 김동진, "선박 조종 시뮬레이션을 위한 단순 기동 모델 개발", 한국시뮬레이션학회 논문지, 19(3), pp.17~25 (2010), 한국시뮬레이션학회
- 김동진, "해석적 방법에 의한 선박 시뮬레이터용 단순 조종 모델 개발", 대한조선학회 논문집, 47(6), pp.776~781 (2010), 대한조선학회
- 김정현, "선박의 이", 접안 데이터 분석을 통한 자동 이, 대한조선학회 논문집, pp.2021, 58(6)[DOI]
- Su-Rim Kim, "Formation Control of Swarming Vessels Using a Virtual Matrix Approach and ISOT Guidance Algorithm", Processes, 9(9), pp.1581~ (2021), MDPI AG[DOI]
- N. Minorsky, "DIRECTIONAL STABILITY OF AUTOMATICALLY STEERED BODIES", Journal of the American Society for Naval Engineers, 34(2), pp.280~309 (1922), Wiley[DOI]
- Nomoto, K., "On the steering qualities of ships", Int. Shipbuild. Prog, 4(35), pp.354~370 (1957)
- 박정홍, "경로 예측의 불확실성을 고려한 무인수상선의 충돌 위험 평가 및 회피 경로 계획", 제어.로봇.시스템학회 논문지, 24(7), pp.608~616 (2018), 제어·로봇·시스템학회[DOI]
- J. Richalet, "Model predictive heuristic control", Automatica, 14(5), pp.413~428 (1978), Elsevier BV[DOI]
- S.S. Sastry, "Adaptive control of linearizable systems", IEEE Transactions on Automatic Control, 34(11), pp.1123~1131 (1989), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
- Son, N. S., "Study on auto-berthing and autodeberthing system of ship using thrusters", J. Korean Soc. Marine Env. Energy, pp.7~14 (2004)
- Sonnenburg, C., "Control-oriented planar motion modeling of unmanned surface vehicles", Proceedings of IEEE international conference on OCEANS, 1, pp.10~ (2010)
- Christian R. Sonnenburg, "Modeling, Identification, and Control of an Unmanned Surface Vehicle", Journal of Field Robotics, 30(3), pp.371~398 (2013), Wiley[DOI]
- Tarbouriech, S., "Lectures Notes in Control and Information Science, vol. 227" (1997), Springer
- Joohyun Woo, "Collision avoidance for an unmanned surface vehicle using deep reinforcement learning", Ocean Engineering, 199, pp.107001~ (2020), Elsevier BV[DOI]
- Joohyun Woo, "Dynamic model identification of unmanned surface vehicles using deep learning network", Applied Ocean Research, 78, pp.123~133 (2018), Elsevier BV[DOI]
- 원문철, "선박 자동 이접안을 위한 비선형 제어알고리즘 연구", 한국해양공학회지, 22(3), pp.34~40 (2008), 한국해양공학회
- H. Yasukawa, "Introduction of MMG standard method for ship maneuvering predictions", Journal of Marine Science and Technology, 20(1), pp.37~52 (2014), Springer Science and Business Media LLC[DOI]
- 윤현규, "RIB형 표적정의 수평면 조종운동 간략모델", 대한조선학회 논문집, 44(6), pp.572~578 (2007), 대한조선학회
- Zhenyu YU, "Course Keeping Control of an Autonomous Boat using Low Cost Sensors", Journal of System Design and Dynamics, 2(1), pp.389~400 (2008), Japan Society of Mechanical Engineers[DOI]
- L.A. Zadeh, "Fuzzy sets", Information and Control, 8(3), pp.338~353 (1965), Elsevier BV[DOI]
- L.A. Zadeh, "Fuzzy algorithms", Information and Control, 12(2), pp.94~102 (1968), Elsevier BV[DOI]