MMG 3DOF model identification with uncertainty of observation and hydrodynamic maneuvering coefficients using MCMC method

Author:

Mitsuyuki TaigaORCID,Kuribayashi Kouki,Fernandez Ricardo Francisco Suarez,Shimozawa Hyuga,Kakuta Ryo,Niki Ryosuke,Matsushita Rintaro

Abstract

AbstractThe trajectory prediction using ship maneuverability mathematical models is one of the essential technologies implemented in autonomous surface ship. Several ship maneuverability mathematical models and each one with a particular hydrodynamic coefficient approximation using towing tank tests are existed. However, it is presented difficult to directly inverse estimate the hydrodynamic maneuvering coefficients of a ship maneuverability mathematical model from operational data consisting of ship trajectory and maneuvering operation records. This paper proposed a method for estimating the hydrodynamic maneuvering coefficients of the MMG 3DOF model using three types of time-series ship motions (surge, sway, and yaw velocity) as observed data. In the assumption of this paper, there is uncertainty in observations and the hydrodynamic maneuvering coefficients of the MMG 3DOF model. The proposed method outputs samples of the simultaneous posterior probability distribution of the hydrodynamic maneuvering coefficients by the MCMC method using the observed data and stochastic model. A robust trajectory with a wide range can be presented by conducting ship maneuvering simulations using these samples. To verify the feasibility of the proposed method, this paper conducted observation system simulation experiments (OSSE) using the KVLCC2 L7 model and applied the proposed method to several free-running model ship tests. Results showed that on the assumption that MMG 3DOF model can explain the ship's state and trajectory in real world, the proposed method can estimate the ship hydrodynamic maneuvering coefficients of the MMG 3DOF model corresponding to the observed ship trajectory and control data including the error of observed data.

Funder

Yokohama National University

Publisher

Springer Science and Business Media LLC

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