基于观测噪声实时估计的卡尔曼滤波车窗防夹系统研究

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。

Anti pinch Window Lifter System Based on Kalman Filter with Real Time Estimation of Measurement Noise

Abstract: 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 the real time estimation of measurement noise. The simulation results in Matlab show that the proposed algorithm can effectively achieve real time estimation of observation noise, and attain better control performance under various noises.