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Highly Nonlinear Flexible Manipulator State Estimation Using the Extended and the Unscented Kalman Filters

机译:使用扩展和无味卡尔曼滤波器的高度非线性柔性机械臂状态估计

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摘要

This paper proposes and compares the state estimation scheme and performance of the Extended Kalman Filter and the Unscented Kalman Filter. A highly nonlinear flexible manipulator is targeted by the study to evaluate the effectiveness and robustness of the proposed filters facing an online accurate estimation problem. An Euler-Bernoulli cantilever beam models the manipulator, and the elastic movement is approximated using the assumed modes method The Hamilton's principle yields the system nonlinear equations. This article compares, via the included numerical simulation results, the efficiency of the state estimate reflected by the estimation error and the time required by the filters to converge.
机译:本文提出并比较了扩展卡尔曼滤波器和无味卡尔曼滤波器的状态估计方案和性能。这项研究的目标是高度非线性的柔性机械手,以评估所提出的滤波器的有效性和鲁棒性,该滤波器面对在线精确估计问题。用Euler-Bernoulli悬臂梁对机械手进行建模,并使用假定模式方法对弹性运动进行近似。汉密尔顿原理产生系统非线性方程。本文通过包含的数值模拟结果,比较了由估计误差反映的状态估计效率和滤波器收敛所需的时间。

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