文献类型：期刊文献

中文题名：基于观测噪声实时估计的卡尔曼滤波车窗防夹系统研究

英文题名：Anti-pinch Window Lifter System Based on Kalman Filter with Real-Time Estimation of Measurement Noise

作者：曹忠[1];李钰[1];王圣伟[1]

机构：[1]华东理工大学信息科学与工程学院,上海200237

年份：2015

卷号：41

期号：3

起止页码：379

中文期刊名：华东理工大学学报（自然科学版）

外文期刊名：Journal of East China University of Science and Technology

收录：CSTPCD;;Scopus;北大核心:【北大核心2014】；CSCD:【CSCD2015_2016】；

语种：中文

中文关键词：卡尔曼滤波;小波变换;噪声估计;车窗防夹

外文关键词：Kalman filtering; wavelet transform; noise estimation; anti-pinch

摘要：卡尔曼滤波可有效解决电机参数变化对车窗防夹控制性能的影响。然而,由于观测噪声往往是未知并且随时间变化,这对基于卡尔曼滤波的车窗防夹控制系统性能有着重要的影响。本文利用小波变换可以对信号和噪声进行分离的特性,提出了一种基于观测噪声实时估计的电动车窗防夹控制方法。在Matlab环境下进行了建模和仿真,结果表明本文算法可以有效实现对观测噪声的实时估计,在不同的噪声条件下都达到了较好的控制效果。
Kalman filter algorithm can effectively cope with the effect of motor parameters in the anti- pinch power window system. However, the observation noise, often unknown and changing in the anti- pinch power window system, has a serious influence on the performance of Kalman filter. By means of the feature of the wavelet transform separating the signal and the noise, this paper proposes a new anti-pinch window lifter system based on Matlab show that the proposed the real-time estimation of measurement noise. The simulation results in algorithm can effectively achieve real-time estimation of observation noise, and attain better control performance under various noises.