估计员
扩展卡尔曼滤波器
应用数学
非线性系统
卡尔曼滤波器
国家(计算机科学)
插值(计算机图形学)
移动视界估计
数学
多项式的
泰勒级数
控制理论(社会学)
计算机科学
数学优化
算法
控制(管理)
人工智能
统计
数学分析
物理
运动(物理)
量子力学
作者
Magnus Nørgaard,Niels Kjølstad Poulsen,Ole Ravn
出处
期刊:Automatica
[Elsevier]
日期:2000-11-01
卷期号:36 (11): 1627-1638
被引量:978
标识
DOI:10.1016/s0005-1098(00)00089-3
摘要
State estimators for nonlinear systems are derived based on polynomial approximations obtained with a multi-dimensional interpolation formula. It is shown that under certain assumptions the estimators perform better than estimators based on Taylor approximations. Nevertheless, the implementation is significantly simpler as no derivatives are required. Thus, it is believed that the new state estimators can replace well-known estimators, such as the extended Kalman filter (EKF) and its higher-order relatives, in most practical applications.
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