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题名:
Adaptive unscented Kalman filter for estimation of modelling errors for helicopter
作者: Song Q(宋崎); He YQ(何玉庆)
作者部门: 机器人学研究室
会议名称: 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO)
会议日期: December 19-23, 2009
会议地点: Guilin, China
会议主办者: IEEE Robotics and Automation Society; National University of Defense Technology; The Chinese University of Hong Kong; City University of Hong Kong
会议录: 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO)
会议录出版者: IEEE Computer Society
会议录出版地: Piscataway, NJ, USA
出版日期: 2009
页码: 2463-2467
收录类别: EI ; CPCI(ISTP)
EI收录号: 20101712895196
WOS记录号: WOS:000285530501213
产权排序: 1
ISBN号: 978-1-4244-4775-6
摘要: In order to overcome the drawback of the normal unscented Kalman filter (UKF) a novel adaptive UKF (AUKF) is developed and applied to nonlinear joint estimation of both time-varying states and modelling errors for helicopter. The filter is composed of two parallel master-slave UKFs, while the master UKF estimates the states/parameters and the slave one estimates the diagonal elements of the noise covariance matrix for the master UKF. Such a mechanism improves the adaptive ability of the UKF and enlarges its application scope. Simulations conducted on the dynamics of helicopter indicate that the performance of the adaptive UKF is superior to the standard one in terms of fast convergence and estimation accuracy.
语种: 英语
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内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/8547
Appears in Collections:机器人学研究室_会议论文

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作者单位: 1.Automation Department, Shenyang Institute of Aeronautical Engineering, 37# Daoyi South street, Shenyang, 110136, China
2.Robotics Laboratory, Shenyang Institute of Automation, Chinese Academy of Sciences, China

Recommended Citation:
Song Q,He YQ. Adaptive unscented Kalman filter for estimation of modelling errors for helicopter[C]. 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO). Guilin, China. December 19-23, 2009.Adaptive unscented Kalman filter for estimation of modelling errors for helicopter.
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