Comparative Evaluation of Rudder Excitation Signals for Bayesian Identification of an MMG Model
Year: 2026
Type: article
Abstract: Accurate maneuvering models are crucial for autonomous ships. Traditional methods such as model tests and CFD analysis require considerable time and cost to construct white-box models, while black-box models lack interpretability. Although system identification using operational data to identify white-box model parameters is efficient, standard maneuvers often lack sufficient excitation signals to yield generalizable models, and random maneuvers are impractical on full-scale ships. This study comparatively examines practical excitation signals that are easily implementable on full-scale ships to obtain informative data. Using pseudo-observation data of a KVLCC2 model ship, hydrodynamic coefficients of the MMG model are identified via a Markov Chain Monte Carlo (MCMC) method to quantify parameter uncertainty while explicitly accounting for observation noise. Among the tested cases, the linearly decreasing rudder-angle signal yielded the most balanced predictive performance for the turning and zig-zag maneuvers. In this numerical case study, the signal covered the full allowable rudder-angle range and generated motions ranging from turning to approximately straight-line behavior. The identified models also retained similar predictive accuracy under a specific synthetic perturbation introduced between the commanded and actual rudder angles. These results indicate that a linearly decreasing rudder-angle signal is a promising candidate for acquiring informative data for MMG model identification.
DOI: 10.3390/jmse14181746
Institution: Yokohama National University
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W7213865645