Real-time parameter identification of ship maneuvering response model based on nonlinear Gaussian Filter
In order to solve the problem of parameter identification of nonlinear ship motion model in ship autonomous navigation control, a real-time parameter identification method based on nonlinear Gaussian filtering algorithm and nonlinear ship response model is proposed. It is proved theoretically that the influence of parameter drift on parameter identification can be reduced by increasing the number of observers and filters, and the system identification accuracy can be improved. The validity of the proposed method is verified by parameter identification experiments based on Zig-zag motion simulation data of Mariner standard ship model. Simulation results show that compared with EKF, the nonlinear Gaussian filter algorithm can effectively improve the parameter identification accuracy and reduce the computational complexity. The application of parallel structure is helpful to improve the identification accuracy and convergence rate of nonlinear Gaussian filter algorithm.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/00298018
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Supplemental Notes:
- © 2021 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
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Authors:
- Wang, Sisi
- Wang, Lijun
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0000-0002-4113-3817
- Im, Namkyun
- Zhang, Weidong
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0000-0002-8165-625X
- Li, Xijin
- Publication Date: 2022-3-1
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
- Pagination: 110471
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Serial:
- Ocean Engineering
- Volume: 247
- Issue Number: 0
- Publisher: Pergamon
- ISSN: 0029-8018
- EISSN: 1873-5258
- Serial URL: http://www.sciencedirect.com/science/journal/00298018
Subject/Index Terms
- TRT Terms: Autonomous vehicle guidance; Kalman filtering; Maneuvering; Navigation; Ships
- Subject Areas: Marine Transportation; Vehicles and Equipment;
Filing Info
- Accession Number: 01840296
- Record Type: Publication
- Files: TRIS
- Created Date: Mar 25 2022 12:36PM