Identification of an underactuated unmanned surface vehicle

Jiang Zhao, Weisheng Yan, Xuelian Jin, Jian Gao

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Hydrodynamic coefficients strongly affect the dynamic performance of underactuated unmanned surface vehicle (USV). Towing tank test is the traditional approach to identify these coefficients, however, the obtained values are not completely reliable since experimental difficulties and errors are involved. In this paper, an extended Kalman filter (EKF) method and a least squares (LS) method are proposed, only using onboard sensor data for identification of a small underactuated USV. The vehicle prototype as well as the system integration is delineated. Performance of the identification is evaluated by comparing the estimated coefficients, and the feasibility and accuracy of the proposed approach is demonstrated by simulation.

Original languageEnglish
Pages (from-to)699-705
Number of pages7
JournalXibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
Volume30
Issue number5
StatePublished - Oct 2012

Keywords

  • Computer simulation
  • Computer software
  • Errors
  • Estimation
  • Experiments
  • Extended Kalman filter
  • Hydrodynamics
  • Identification (control systems)
  • Kalman filters
  • Least squares approximations
  • Mathematical models
  • Measurement errors
  • Sensors

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