Sigma-point Smooth Variable Structure Filters applications into robotic arm

摘要

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.