摘要
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.
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.
出处
《西北工业大学学报》
EI
CAS
CSCD
北大核心
2012年第5期699-705,共7页
Journal of Northwestern Polytechnical University
关键词
工业大学
教学管理
教育事业
教育发展
Computer simulation, Computer software, Errors, Estimation, Experiments, Hydrodynamics, Identification （ control systems）, Kalman filters, Least squares approximations, Mathematical models, Measurement errors, Sensors
Extended Kalman filter, Underactuated unmanned surface vehicle
