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题名:
A comparison of nonlinear estimation methods for tracked vehicle with slipping
作者: Zhou B(周波); Han JD(韩建达)
作者部门: 机器人学研究室
会议名称: IEEE International Conference on Control and Automation
会议日期: May 30-June 1, 2007
会议地点: Guangzhou, China
会议主办者: IEEE
会议录: 2007 IEEE INTERNATIONAL CONFERENCE ON CONTROL AND AUTOMATION, VOLS 1-7
会议录出版者: IEEE
会议录出版地: NEW YORK
出版日期: 2007
页码: 389-394
收录类别: EI ; CPCI(ISTP)
ISBN号: 978-1-4244-0817-7
关键词: nonlinear joint estimation ; tracked vehicle ; Kalman filter ; particle filter ; set-membership
摘要: Four different nonlinear filters are used to estimate both states and time-varying slipping parameters of the created kinematic model of a tracked vehicle. The first filter is the well-known extended Kalman filter. The second filter is a recent development of unscented version of the Kalman filter. The third one is a particle filter using the unscented Kalman filter to generate the importance proposal distribution. The last one is a novel and guaranteed filter that use a linear set-membership estimator and can give an ellipsoid set in which the true state lies. The four different approaches have different complexities, behavior and advantages that are compared in simulations.
语种: 英语
产权排序: 1
EI收录号: 20082311291168
WOS记录号: WOS:000257195302104
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/8469
Appears in Collections:机器人学研究室_会议论文

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Recommended Citation:
Zhou B,Han JD. A comparison of nonlinear estimation methods for tracked vehicle with slipping[C]. IEEE International Conference on Control and Automation. Guangzhou, China. May 30-June 1, 2007.A comparison of nonlinear estimation methods for tracked vehicle with slipping.
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