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Zigzag maneuvering test and trained neural network as tools for adequate identification of the mathematical model of vessel motion
DOI: 10.21443/1560-9278-2025-28-4/1-558-571
Abstract. The neural network is applied for correction of the mathematical model of vessel motion. The data obtained during the model tests in the standard maneuver mode "zigzag 20/20" have been used for its training. The data set training the neural network has been obtained by means of random variations with normal distribution of the initially calculated parameters of the model. During the computer tests of the varied model, the measurable kinematic parameters for the characteristic moments of maneuvering have been recorded. These are the moments of the beginning of the rudder throwing from side to side and the moments of the subsequent maximum yawing of the vessel. For six such moments, seven parameters are saved: time, linear speed, angular rate of turn, course and coordinates of the vessel (42 input data for network training). In the Statistica Neural Nets (SNN) software environment, the network has been trained on the basis of 600 sets of such data using the IPS intelligent problem solver built into the SNN environment. The listed data are the network input, and the output ones are the parameters of the mathematical model. The network trained in this way allows for the given maneuvering characteristics, for example, determined by full-scale tests, to find a set of model parameters. If it is necessary to correct the model to meet the changed maneuvering requirements, using them as input to the already trained network, at the output we will obtain a set of model parameters adequate to these changed requirements. The most complex mathematical model in movements is considered, which is expanded to 19 parameters by additionally including two coefficients of added masses and the added moment of inertia of the vessel. All this makes it possible to obtain refined parameters of the mathematical model of the vessel's motion as output variables of the network. The analysis of the results allows us to draw a number of conclusions about the applicability of this approach and the degree of its effectiveness.
Printed reference: Pashentsev S. V. Zigzag maneuvering test and trained neural network as tools for adequate identification of the mathematical model of vessel motion // Vestnik of MSTU. 2025. V. 28, No 4. P. 558-571.
Electronic reference: Pashentsev S. V. Zigzag maneuvering test and trained neural network as tools for adequate identification of the mathematical model of vessel motion // Vestnik of MSTU. 2025. V. 28, No 4. P. 558-571. URL: https://vestnik.mauniver.ru/v28_4_1_n105/10_Pashentsev_558-571.pdf.
