sigma点光滑变结构滤波器在机械臂中的应用

M. Al-Shabi
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引用次数: 24

摘要

在这项工作中,众所周知的西格玛点卡尔曼滤波器(SPKFs);即Unscented卡尔曼滤波器(UKF), Cubature卡尔曼滤波器(CKF)和中心差分卡尔曼滤波器(CDKF)将结合到光滑变结构滤波器(SVSF)中,以创建稳定和鲁棒的算法,可应用于高度非线性系统。该算法将应用于由一个移动关节和三个旋转关节组成的四自由度机械臂。通过这样做,所提出的滤波器的稳定性将得到保证。这使得SPKFs之间的比较更加容易。这些方法将通过仿真实验来执行,然后在稳定性、鲁棒性和最优性质量方面进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sigma-point Smooth Variable Structure Filters applications into robotic arm
In this work, well known Sigma Point Kalman Filters (SPKFs); namely Unscented Kalman filter (UKF), the Cubature Kalman filter (CKF), and the Central Differences Kalman filter (CDKF) will be combined to the Smooth Variable Structure Filter (SVSF), in order to create stable and robust algorithms that can be applied to highly non-linear systems. The proposed algorithms will be applied into 4-DOF robotic arm that consists of one prismatic joint and three revolute joints (PRRR). By doing so, the stability of the proposed filters will be guaranteed. Which makes the comparison between the SPKFs easier. These methods will be executed using simulation experiments, and then they will be compared in terms of stability, robustness and the quality of the optimality.
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