The Least-square support vector machine (LS-SVM) is used to estimate the dynamic parameters of a nonlinear marine vessel steering model in real-time. First, manoeuvring tests are carried out based on a scaled free-running ship model. The parameters are estimated using standard LS-SVM and compared with the theoretical solutions. Then, an online version, a sequential least square support vector machine, is derived and used to estimate the parameters of vessel steering in real-time. The results are compared with the values estimated by standard LS-SVM with batched training data. By comparison, sequential least square support vector machine can dynamically estimate the parameters successfully, and it can be used for designing a dynamic model-based controller of marine vessels.
- Ocean, Offshore and Arctic Engineering Division
Real-Time Parameter Estimation of Nonlinear Vessel Steering Model Using Support Vector Machine
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Xu, H, Hassani, V, Hinostroza, MA, & Guedes Soares, C. "Real-Time Parameter Estimation of Nonlinear Vessel Steering Model Using Support Vector Machine." Proceedings of the ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering. Volume 11B: Honoring Symposium for Professor Carlos Guedes Soares on Marine Technology and Ocean Engineering. Madrid, Spain. June 17–22, 2018. V11BT12A009. ASME. https://doi.org/10.1115/OMAE2018-78234
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