Adaptive modeling of maritime autonomous surface ships with uncertainty using a weighted LS-SVR robust to outliers
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Axel Hahn | Changshi Xiao | Yuanqiao Wen | Man Zhu | Wei Tao | Wuqiang Sun | A. Hahn | Changshi Xiao | Y. Wen | Man Zhu | Wei Tao | Wuqiang Sun
[1] K Nomoto. On the steering qualities of ships , 1957 .
[2] Yuanqiao Wen,et al. A Novel Adaptive Weighted Least Square Support Vector Regression Algorithm-Based Identification of the Ship Dynamic Model , 2019, IEEE Access.
[3] Man Zhu,et al. Identification-based simplified model of large container ships using support vector machines and artificial bee colony algorithm , 2017 .
[4] C. Guedes Soares,et al. Vector Field Path Following for Surface Marine Vessel and Parameter Identification Based on LS-SVM , 2016 .
[5] Johan A. K. Suykens,et al. Least Squares Support Vector Machine Classifiers , 1999, Neural Processing Letters.
[6] Guofeng Wang,et al. Modeling and Identification for Vector Propulsion of an Unmanned Surface Vehicle: Three Degrees of Freedom Model and Response Model , 2018, Sensors.
[7] Stein Haugen,et al. Assessing ship risk model applicability to Marine Autonomous Surface Ships , 2018, Ocean Engineering.
[8] Tiranee Achalakul,et al. The best-so-far selection in Artificial Bee Colony algorithm , 2011, Appl. Soft Comput..
[9] Yoshiho Ikeda,et al. A Simple Prediction Formula of Roll Damping of Conventional Cargo Ships on the Basis of Ikeda's Method and Its Limitation , 2011 .
[10] Xue-feng Yan,et al. Adaptive weighted least square support vector machine regression integrated with outlier detection and its application in QSAR , 2009 .
[11] Meng Joo Er,et al. Large Tanker Motion Model Identification Using Generalized Ellipsoidal Basis Function-Based Fuzzy Neural Networks , 2015, IEEE Transactions on Cybernetics.
[12] C. Guedes Soares,et al. Identification of ship manoeuvring motion based on nu-support vector machine , 2019, Ocean Engineering.
[13] C. Soares,et al. An algorithm for offline identification of ship manoeuvring mathematical models from free-running tests , 2014 .
[14] C. Guedes Soares,et al. Hydrodynamic coefficient estimation for ship manoeuvring in shallow water using an optimal truncated LS-SVM , 2019, Ocean Engineering.
[15] Xiaodong Liu,et al. Ship Maneuvering Prediction Using Grey Box Framework via Adaptive RM-SVM with Minor Rudder , 2019, Polish Maritime Research.
[16] Weilin Luo,et al. Control for Ship Course-Keeping Using Optimized Support Vector Machines , 2016, Algorithms.
[17] Sanjay Sharma,et al. Non-linear control algorithms for an unmanned surface vehicle , 2014 .
[18] Tristan Perez,et al. Ship Motion Control: Course Keeping and Roll Stabilisation Using Rudder and Fins , 2005 .
[19] Ronald K. Pearson,et al. Outliers in process modeling and identification , 2002, IEEE Trans. Control. Syst. Technol..
[20] Petre Stoica,et al. Decentralized Control , 2018, The Control Systems Handbook.
[21] R. A. Shenoi,et al. Global marine technology trends 2030 , 2015 .
[22] Marc Vantorre,et al. Parameter estimation for a ship's roll response model in shallow water using an intelligent machine learning method , 2019 .
[23] Liping Sun,et al. Parameter Identification of the Non-Linear Rolling Damping Based on PLS Regression Technique , 2013 .
[24] Metin Kemal Gokce,et al. Numerical simulations of free roll decay of DTMB 5415 , 2018, Ocean Engineering.
[25] Rafal Szlapczynski,et al. High performance super-twisting sliding mode control for a maritime autonomous surface ship (MASS) using ADP-Based adaptive gains and time delay estimation , 2019, Ocean Engineering.
[26] Vladimir Shigunov,et al. Energy Efficient Safe SHip Operation (SHOPERA) , 2016 .
[27] Lokukaluge P. Perera,et al. System Identification of Vessel Steering With Unstructured Uncertainties by Persistent Excitation Maneuvers , 2016, IEEE Journal of Oceanic Engineering.
[28] Benedetto Allotta,et al. Redundant and reconfigurable propulsion systems to improve motion capability of underwater vehicles , 2018 .
[29] Zao-Jian Zou,et al. Nonparametric identification of nonlinear ship roll motion by using the motion response in irregular waves , 2018 .
[30] Gene H. Golub,et al. Singular value decomposition and least squares solutions , 1970, Milestones in Matrix Computation.
[31] Johan A. K. Suykens,et al. Weighted least squares support vector machines: robustness and sparse approximation , 2002, Neurocomputing.
[32] Joaquín Aranda Almansa,et al. Identification of a Surface Marine Vessel Using LS-SVM , 2013, J. Appl. Math..
[33] Xianku Zhang,et al. Multi-innovation auto-constructed least squares identification for 4 DOF ship manoeuvring modelling with full-scale trial data. , 2015, ISA transactions.
[34] Benedetto Allotta,et al. Identification of the main hydrodynamic parameters of Typhoon AUV from a reduced experimental dataset , 2018 .
[35] Giulio Dubbioso,et al. Method for estimating parameters of practical ship manoeuvring models based on the combination of RANSE computations and System Identification , 2015 .
[36] Ali Mosleh,et al. Human-system concurrent task analysis for maritime autonomous surface ship operation and safety , 2020, Reliab. Eng. Syst. Saf..
[37] Thor I. Fossen,et al. Handbook of Marine Craft Hydrodynamics and Motion Control , 2011 .
[38] Mukhtiar Ali Unar,et al. Automatic steering of ships using neural networks , 1999 .
[39] Axel Hahn,et al. Optimized support vector regression algorithm-based modeling of ship dynamics , 2019, Applied Ocean Research.
[40] Ingrid Bouwer Utne,et al. Collision avoidance on maritime autonomous surface ships: Operators’ tasks and human failure events , 2019, Safety Science.
[41] Anna Witkowska,et al. Marine autonomous surface ship - control system configuration , 2019 .
[42] C. Guedes Soares,et al. Parameter Identification of Ship Maneuvering Model Based on Support Vector Machines and Particle Swarm Optimization , 2016 .
[43] Dervis Karaboga,et al. A comparative study of Artificial Bee Colony algorithm , 2009, Appl. Math. Comput..
[44] Qiang Li,et al. Improved Maximum Likelihood Method for Ship Parameter Identification , 2018, 2018 37th Chinese Control Conference (CCC).
[45] Naoya Umeda,et al. Estimating maneuvering coefficients using system identification methods with experimental, system-based, and CFD free-running trial data , 2012 .
[46] Mohammad Bozorg,et al. Robust estimation of hydrodynamic coefficients of an AUV using Kalman and H∞ filters , 2019, Ocean Engineering.