Roll prediction and parameter identification of marine vessels under unknown ocean disturbances

• Autorzy: Lee, Sang-Do , Kim, Hwan-Seong , You, Sam-Sang , Yeon, Jeong-Hum , Bui, Duc Hong Phuc
• Języki publikacji: EN

Abstrakty

EN

This paper deals with two topics: roll predictions of marine vessels with machine-learning methods and parameter estimation of unknown ocean disturbances when the amplitude, frequency, offset, and phase are difficult to estimate. This paper aims to prevent the risky roll motions of marine vessels exposed to harsh circumstances. First of all, this study demonstrates complex dynamic phenomena by utilising a bifurcation diagram, Lyapunov exponents, and a Poincare section. Without any observers, an adaptive identification applies these four parameters to the globally exponential convergence using linear second-order filters and parameter estimation errors. Then, a backstepping controller is employed to make an exponential convergence of the state variables to zero. Finally, this work presents the prediction of roll motion using reservoir computing (RC). As a result, the RC process shows good performance for chaotic time series prediction in future states. Thus, the poor predictability of Lyapunov exponents may be overcome to a certain extent, with the help of machine learning. Numerical simulations validate the dynamic behaviour and the efficacy of the proposed scheme.

Słowa kluczowe

EN

non-periodic roll motions; dynamic analysis; reservoir-computing; parameter Estimation; periodic disturbances; backstepping

• Czasopismo: Polish Maritime Research
• Rocznik: 2024
• Tom: nr 1
• Strony: 4--15
• Opis fizyczny: Bibliogr. 22 poz., rys., tab.

Twórcy

autor

Lee, Sang-Do

• Division of Navigation & Information System, Mokpo National Maritime University, Republic of Korea

autor

Kim, Hwan-Seong

• Division of Logistics, Korea Maritime and Ocean University, Republic of Korea,

autor

You, Sam-Sang

• Northeast-Asia Shipping and Port Logistics Research Center, Korea Maritime and Ocean University, Republic of Korea

autor

Yeon, Jeong-Hum

• R&D Department, Busan Port Authority, Republic of Korea

autor

Bui, Duc Hong Phuc

• Department of Engineering Technology, Gadomski School of Engineering, Christian Brothers University, United States

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Identyfikatory

DOI

10.2478/pomr-2024-0001