期刊论文

Model Error Compensation of Double-fading Kalman Filtering to Rectangular Board of Six-axis Force Sensors

中文

机械科学与技术

1003-8728

2019

38

4

594-600

10.13433/j.cnki.1003-8728.20180207

61473272:国家自然科学基金 61403362:国家自然科学基金 61301060:国家自然科学基金

本校为第一机构

六维力传感器能够通过应变片及板梁结构实时检测空间六方向的力信息,但其输出信号不可避免地被噪声干扰所污染。为改善这一现象,同时针对过程噪声模型不精准致使经典卡尔曼滤波器性能差的问题,设计了一种双因子渐消卡尔曼滤波器。算法研究了加性噪声信号的统计特性,建立了矩形板主振型增广状态方程,分析了两种过程噪声模型偏差对滤波性能的影响。在经典卡尔曼滤波器的基础上,基于新息正交性原理,依据Sage开窗估计原理与最小二乘准则,构造了双渐消因子的解析式,阐述了滤波器的工作原理。研究表明:双渐消卡尔曼滤波器稳定性强,能够有效削弱噪声模型偏差的影响;对比抗差卡尔曼滤波器,精度提升38.66...

The six-axis force sensors can detect spatial force information in six directions in real time through the strain gauge and plate girder structure, but the output signal is inevitably polluted by the noise signal. In order to improve this phenomenon, a kind of double-fading factors Kalman filter is designed for the problem of poor performance of the standard Kalman filter due to the inaccuracy of the acoustic noise model. The statistical properties of the additive noise signal are studied in this algorithm. The augmented state equation of the principal mode shape of the rectangular plate is es...