An Approach for System Identification in Unmanned Surface Vehicles

Date

2017-10-21

Author

Erunsal, Izzet Kagan
Ahiska, Kenan
Kumru, Murat
Leblebicioğlu, Mehmet Kemal

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In this study, a system identification methodology is introduced to determine the model parameters of unmanned surface vehicles. The proposed identification scheme is based on sequencing the experiments according to their capabilities to identify the model parameters. In each experiment, the parameters to be found are updated and the results are validated before ascertaining the final value. A procedure to complete the identification work in an experiment, namely the required post-processing, the optimization routines, the cost function evaluations are defined and discussed. The final parameter set is validated in random motion tests with rich motion content. It has been observed that the proposed method elicits a parameter identification with remarkable success.

Subject Keywords

Unmanned surface vehicles, Parameter estimation, System identification, Unmanned surface vehicles

URI

https://hdl.handle.net/11511/54275

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

I. K. Erunsal, K. Ahiska, M. Kumru, and M. K. Leblebicioğlu, “An Approach for System Identification in Unmanned Surface Vehicles,” 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54275.