A Study Evaluating the Performance of Nonlinear Nomoto Models in Predicting the Manoeuvring of Car Carrier

This study evaluates the performance of first and second-order nonlinear Nomoto models in predicting the manoeuvrability of car carriers. These large vessels require precise manoeuvring models to ensure safe and efficient navigation, especially in confined or congested waters. The Nomoto model, a standard tool for predicting ship dynamics, is extended to nonlinear versions to better capture the complex behaviours of large ships. The performance of both first and second-order models is analysed through the simulation of standard manoeuvres, comparing their accuracy, stability, and computational efficiency. The models were developed using the grey-box method to estimate their coefficients, leveraging both physical understanding and data-driven techniques. The results demonstrate that while both models provide valuable insights, second-order models offer improved accuracy in dynamic manoeuvres, albeit with higher computational demands.