“Modeling and Analyzing the Impact of Environmental Disturbances in Vessel Model Estimation”
Authors: Beatriz Sanguino, Tongtong Wang, Guoyuan Li, Øyvind Kåre Kjerstad and Houxiang Zhang,Affiliation: NTNU Aalesund
Reference: 2025, Vol 46, No 1, pp. 35-49.
Keywords: Maneuvering Model; External disturbances; Parameter Estimation; Least Square Regression; Sensitivity Analysis
Abstract: Environmental disturbances such as wind, currents, and waves introduce uncertainties in hydrodynamic parameter estimation, affecting the accuracy of ship maneuvering models and trajectory prediction. This study investigates how these disturbances influence the estimation of hydrodynamic derivatives in the Abkowitz maneuvering model and their impact on their accuracy. Therefore, models are estimated using least squares regression based on data from four maneuvers conducted under different wind and current conditions. A comparison of the resulting hydrodynamic derivatives identifies parameters that exhibit greater variance as disturbance intensity increases. To further assess their influence on the trajectory prediction error, Sobol sensitivity analysis is applied to determine which parameter variations most significantly affect trajectory accuracy. The results reveal that while some parameters remain stable across environmental conditions, others exhibit slight variations. Additionally, the parameters most affected by disturbances are not necessarily those with the greatest impact on trajectory prediction error. These findings highlight the importance of accounting for environmental effects in vessel model estimation to improve prediction reliability and provide deeper insight into how disturbances impact the model estimation process.
PDF (2475 Kb)
DOI: 10.4173/mic.2025.1.3References:
[1] Abkowitz, M. (1964). Lectures on Ship Hydrodynamics - Steering and Manoeuvrability, Hydro of Aerodynamisk Laboratorium.
[2] Bar-Shalom, Y., Li, X.R., and Kirubarajan, T. (2001). Estimation with Applications to Tracking and Navigation, John Wiley & Sons.
[3] Blendermann, W. (1994). Parameter identification of wind loads on ships, Journal of Wind Engineering and Industrial Aerodynamics. 51(3):339--351. doi:10.1016/0167-6105(94)90067-1
[4] Chen, L., Yang, P., Li, S., Tian, Y., Liu, G., and Hao, G. (2022). Grey-box identification modeling of ship maneuvering motion based on ls-svm, Ocean Engineering. 266:112957. doi:10.1016/j.oceaneng.2022.112957
[5] Clarke, D., Gedling, P., and G.Hine. (1982). The application of manoeuvring criteria in hull design using linear theory, The Royal Institution of Naval Architects.
[6] Costa, A., Xu, H., and GuedesSoares, C. (2021). Robust parameter estimation of an empirical manoeuvring model using free-running model tests, Journal of Marine Science and Engineering. 9:1302. doi:10.3390/jmse9111302
[7] Du, P., Cheng, L., Tang, Z.-j., Ouahsine, A., Hu, H.-b., and Hoarau, Y. (2022). Ship maneuvering prediction based on virtual captive model test and system dynamics approaches, Journal of Hydrodynamics. 34. doi:10.1007/s42241-022-0029-0
[8] Fossen, T.I. (2011). Handbook of Marine Craft Hydrodynamics and Motion Control, John Wiley & Sons, Ltd.
[9] Li, S., Wang, T., Li, G., and Zhang, H. (2023). Ship maneuvering model optimization for improved identification with less excitation, Ocean Engineering. 280:114540. doi:10.1016/j.oceaneng.2023.114540
[10] Liu, Y., Zou, L., and Zou, Z. (2019). Computational fluid dynamics prediction of hydrodynamic forces on a manoeuvring ship including effects of dynamic sinkage and trim, Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment. 233(1):251--266. doi:10.1177/1475090217734685
[11] Luo, W. and Li, X. (2017). Measures to diminish the parameter drift in the modeling of ship manoeuvring using system identification, Applied Ocean Research. 67:9--20. doi:10.1016/j.apor.2017.06.008
[12] Luo, W. and Zou, Z. (2009). Parametric identification of ship maneuvering models by using support vector machines, Journal of Ship Research. 53:19--30. doi:10.5957/jsr.2009.53.1.19
[13] Obreja, D., Nabergoj, R., Crudu, L., and Păcuraru-Popoiu, S. (2010). Identification of hydrodynamic coefficients for manoeuvring simulation model of a fishing vessel, Ocean Engineering. 37(8):678--687. doi:10.1016/j.oceaneng.2010.01.009
[14] Ogawa, A. and Kasai, H. (1978). On the mathematical model of manoeuvring motion of ships, International shipbuilding progress. 25:306--319.
[15] Perera, L., Oliveira, P., and Soares, C.G. (2015). System identification of nonlinear vessel steering, Journal of Offshore Mechanics and Arctic Engineering. 137. doi:10.1115/1.4029826
[16] Perera, L., Oliveira, P., and Soares, C.G. (2016). System identification of vessel steering with unstructured uncertainties by persistent excitation maneuvers, IEEE Journal of Oceanic Engineering. 41:515--527. doi:10.1109/JOE.2015.2460871
[17] Sobol, I. (2001). Global sensitivity indices for nonlinear mathematical models and their monte carlo estimates, Mathematics and Computers in Simulation.
[18] Soeding, H. (1982). Prediction of ship steering capabilities, 1982. 29:3--29.
[19] Wang, T., Æsøy, V., and Zhang, H. (2021). Parameter identification of ship manoeuvring model under disturbance using support vector machine method, Ships and Offshore Structures. 16. doi:10.1080/17445302.2021.1927600
[20] Wang, Z., Xu, H., Xia, L., Zou, Z., and Soares, C.G. (2020). Kernel-based support vector regression for nonparametric modeling of ship maneuvering motion, Ocean Engineering. 216:107994. doi:10.1016/j.oceaneng.2020.107994
[21] Wang, Z. and Zou, Z. (2018). Quantifying Multicollinearity in Ship Manoeuvring Modeling by Variance Inflation Factor, volume Volume 7A: Ocean Engineering of International Conference on Offshore Mechanics and Arctic Engineering. 2018. doi:10.1115/OMAE2018-77121
[22] Xu, H., Silva, P., and GuedesSoares, C. (2024). Effect of sampling rate in sea trial tests on the estimation of hydrodynamic parameters for a nonlinear ship manoeuvring model, Journal of Marine Science and Engineering. 12:407. doi:10.3390/jmse12030407
[23] Xu, H. and Soares, C.G. (2025). Review of system identification for manoeuvring modelling of marine surface ships, Journal of Marine Science and Application. doi:10.1007/s11804-025-00681-w
[24] Xu, P.-F., Cheng, C., Cheng, H.-X., Shen, Y.-L., and Ding, Y.-X. (2020). Identification-based 3 dof model of unmanned surface vehicle using support vector machines enhanced by cuckoo search algorithm, Ocean Engineering. 197:106898. doi:10.1016/j.oceaneng.2019.106898
[25] Xue, Y., Liu, Y., Ji, C., and Xue, G. (2020). Hydrodynamic parameter identification for ship manoeuvring mathematical models using a bayesian approach, Ocean Engineering. 195:106612. doi:10.1016/j.oceaneng.2019.106612
[26] Yang, Y., Chillcce, G., and Moctar, O. (2023). Mathematical modeling of shallow water effects on ship maneuvering, Applied Ocean Research. 136:103573. doi:10.1016/j.apor.2023.103573
[27] Yang, Y. and elMoctar, O. (2024). A mathematical model for ships maneuvering in deep and shallow waters, Ocean Engineering. 295:116927. doi:10.1016/j.oceaneng.2024.116927
[28] Zhang, S., Wu, Q., Liu, J., He, Y., and Li, S. (2023). State-of-the-art review and future perspectives on maneuvering modeling for automatic ship berthing, Journal of Marine Science and Engineering. 11. doi:10.3390/jmse11091824
[29] Zhu, M., Wang, T., Zhang, H., and Li, G. (2022). Ship manoeuvring model identification under wind disturbance, In 2022 IEEE International Conference on Real-time Computing and Robotics (RCAR). pages 648--653. doi:10.1109/RCAR54675.2022.9872289
[30] Åström, K. and Källström, C. (1976). Identification of ship steering dynamics, Automatica. 12(1):9--22. doi:10.1016/0005-1098(76)90064-9
BibTeX:
@article{MIC-2025-1-3,
title={{Modeling and Analyzing the Impact of Environmental Disturbances in Vessel Model Estimation}},
author={Sanguino, Beatriz and Wang, Tongtong and Li, Guoyuan and Kjerstad, Øyvind Kåre and Zhang, Houxiang},
journal={Modeling, Identification and Control},
volume={46},
number={1},
pages={35--49},
year={2025},
doi={10.4173/mic.2025.1.3},
publisher={Norwegian Society of Automatic Control}
};