Mathematical modeling and identification of surface vessel model parameters

• Main Authors: Khac Tung Nguyen, Sergey M. Vlasov, Aleksandra V. Skobeleva
• Format: Article
• Language: English
• Published: Saint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University) 2021-06-01
• Series: Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki
• Subjects: surface ship; identification; nomoto model; drem; gradient descent method; regressor
• Online Access: https://ntv.ifmo.ru/file/article/20513.pdf
• ISSN: 2226-1494; 2500-0373

The paper considers the problems of modeling and identification of parameters for models of surface ships. The proposed identification method is applied to a modified second order Nomoto model for ship steering. The identification algorithm is based on the Dynamic Regressor Extension and Mixing Method (DREM) that is performed in two steps. At the first stage parameterization is used for a regression model, in which the regressor and regression depend on the measured signals, namely, longitudinal, lateral and angular velocities and steering angle. At the second stage a new regression model is built using linear stable filters and delays. Finally, the parameters are estimated by the standard gradient descent method. The paper proposes a new algorithm which identifies the parameters for models of surface ships. The authors analyzed the prospects of the proposed estimating method by computer experiments. Experiments have shown the advantage of the method: when using the gradient descent method, the transient time spent to estimate the signal parameters is much longer than using the DREM method. At the same time, in the case of using the DREM method, there is no overshoot. The results of the work can serve as a basis for methods, algorithms and software for designing ship automated navigation systems and control systems for other modes of transport. This is confirmed by the simulation results.