New Weighted Adaptive Unscented Kalman Filter for Estimation of Hydraulic Systems

被引：0

作者：

Asl, Reza Mohammadi ^{[1
]}

Handroos, Heikki ^{[1
]}

机构：

[1] Lappeenranta Univ Technol, Lab Intelligent Machines, Lappeenranta, Finland

来源：

2018 GLOBAL FLUID POWER SOCIETY PHD SYMPOSIUM (GFPS) | 2018年

关键词：

Unscented Kalman filter; Hydraulic systems; State estimation; Time varying noise; STATE ESTIMATION; LINEAR-SYSTEMS; UNKNOWN INPUT; OBSERVER; DESIGN;

D O I：

暂无

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

In this paper, a new weighted adaptive unscented Kalman filter is introduced. The proposed filter is trying to improve the performance of the previous versions. To have better results, it uses the previous estimation parameters to update itself. The proposed Kalman filter is applied to estimate the states of the nonlinear systems under time varying noise with time varying statistics. A hydraulic system, as a nonlinear system, is used as an application for the simulation. The results of the simulation are given.

引用

页数：6

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