Abstract
This paper addresses a problem of parametric identification in marine applications, namely, surface vessels equipped with gyrostabilizers. In this work three approaches are considered: the gradient method, Kalman filter-based method and dynamic regressor extension and mixing (DREM) method. All of them are applied to a ship roll motion model with unknown parameters. For simulation of the system, two types of input signals are injected to test sensitivity of the each approach to the persistency of excitation conditions. Simulation results show advantages of the DREM method in the considered application, in particular, with regard to the convergence rate of the multiple parameters estimation.
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Acknowledgments
This work is supported by the Russian Science Foundation (project 19-19-00403).
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Kakanov, M.A., Karashaeva, F.B., Borisov, O.I., Gromov, V.S. (2020). Multiple Parameters Estimation of Ship Roll Motion Model with Gyrostabilizer. In: Arseniev, D., Overmeyer, L., Kälviäinen, H., Katalinić, B. (eds) Cyber-Physical Systems and Control. CPS&C 2019. Lecture Notes in Networks and Systems, vol 95. Springer, Cham. https://doi.org/10.1007/978-3-030-34983-7_31
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DOI: https://doi.org/10.1007/978-3-030-34983-7_31
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