Convergence analysis of hydrodynamic coefficients estimation using regularization filter functions on free-running ship model tests with noise

This paper introduces an effective method with a regularization filter function and conducts stability and convergence analysis for the estimation of the hydrodynamic coefficients of a manoeuvring model. The proposed method is used to estimate the adjustment coefficients of empirical manoeuvring models using free-running manoeuvring ship model tests. The method avoids the recurrent difficulty that parameter estimation based on test data are usually ill-conditioned, and the obtained parameters are unstable and sensitive to noise. The model tests are carried out using a free-running scaled container ship, and the data acquisition and control system is implemented in the LabVIEW platform. Then, the obtained data are used for the parameter estimation using the proposed method and the optimal regularization factor is discussed. Validation is carried out and shows the effectiveness of the proposed method.

Automated summary

This paper introduces an effective method for estimating the hydrodynamic coefficients of a manoeuvring model, and conducts stability and convergence analysis. The proposed method overcomes the common ill-conditioned issues in parameter estimation and demonstrates high robustness to noise. Experimental data from free-running ship model tests are used for parameter estimation, and the effectiveness of the proposed method is validated.