Sequential measurement processing is of benefit to both estimation accuracy and computational efficiency. When the noises are correlated across the measurement components, decorrelation based on covariance matrix fact...Sequential measurement processing is of benefit to both estimation accuracy and computational efficiency. When the noises are correlated across the measurement components, decorrelation based on covariance matrix factorization is required in the previous methods in order to perform sequential updates properly. A new sequential processing method, which carries out the sequential updates directly using the correlated measurement components, is proposed. And a typical sequential processing example is investigated, where the converted position measure- ments are used to estimate target states by standard Kalman filtering equations and the converted Doppler measurements are then incorporated into a minimum mean squared error （MMSE） estimator with the updated cross-covariance involved to account for the correlated errors. Numerical simulations demonstrate the superiority of the proposed new sequential processing in terms of better accuracy and consistency than the conventional sequential filter based on measurement decorrelation.展开更多
针对无迹卡尔曼滤波(unscented Kalman filter,UKF)算法估计锂电池荷电状态(state of charge,SOC)时精度低、稳定性差、产生的sigma点过多导致计算难度大等不足,提出一种基于自适应球形不敏变换方式的无迹卡尔曼滤波(unscented Kalman f...针对无迹卡尔曼滤波(unscented Kalman filter,UKF)算法估计锂电池荷电状态(state of charge,SOC)时精度低、稳定性差、产生的sigma点过多导致计算难度大等不足,提出一种基于自适应球形不敏变换方式的无迹卡尔曼滤波(unscented Kalman filter based on adaptive spherical insensitive transformation,ASIT-UKF)算法。该算法通过使用球形不敏变换方式选择权系数以及初始化一元向量对sigma点的产生进行选取。与UKF算法相比,ASIT-UKF算法产生的sigma点减少近50%,使得算法的计算复杂度大大降低。同时,将产生的所有sigma点进行单位球形面上的归一化处理,提高了数值的稳定性。考虑到实际运行中锂电池系统噪声干扰带来的不确定性,加入Sage-Husa自适应滤波器对不确定性噪声的干扰进行实时更新和修正,以达到提高在线锂电池SOC估计精度的目的。最后,将均方根误差和最大绝对误差计算公式引入到性能估计指标中。实验结果表明,ASIT-UKF算法在准确度、鲁棒性和收敛性方面具有优越的性能。展开更多
动态电压恢复器(dynamic voltage restorer,DVR)的响应速度是衡量DVR特性的重要指标,锁相环和电压跌落检测算法则是决定其响应速度的2个关键因素,而电网电压畸变、跌落过程中发生的相位跳变和电压不平衡制约着锁相环和检测算法的快速性...动态电压恢复器(dynamic voltage restorer,DVR)的响应速度是衡量DVR特性的重要指标,锁相环和电压跌落检测算法则是决定其响应速度的2个关键因素,而电网电压畸变、跌落过程中发生的相位跳变和电压不平衡制约着锁相环和检测算法的快速性。该文结合最小方差(least error squares,LES)滤波器和改进对称分量法设计了新的软件锁相环和电压跌落检测算法,对这2种方法进行详细的理论推导,阐明各频次的正负序分量解耦的机理。在Matlab/Simulink中搭建仿真模型,与传统锁相环方法和电压跌落检测算法进行对比分析。最后,在电压跌落平台进行工业样机验证,结果表明所提方法可行有效,且具有较高的响应速度。展开更多
基金supported by the National Natural Science Foundation of China(6120131161132005)the Aerospace Science Foundation of China(20142077010)
文摘Sequential measurement processing is of benefit to both estimation accuracy and computational efficiency. When the noises are correlated across the measurement components, decorrelation based on covariance matrix factorization is required in the previous methods in order to perform sequential updates properly. A new sequential processing method, which carries out the sequential updates directly using the correlated measurement components, is proposed. And a typical sequential processing example is investigated, where the converted position measure- ments are used to estimate target states by standard Kalman filtering equations and the converted Doppler measurements are then incorporated into a minimum mean squared error （MMSE） estimator with the updated cross-covariance involved to account for the correlated errors. Numerical simulations demonstrate the superiority of the proposed new sequential processing in terms of better accuracy and consistency than the conventional sequential filter based on measurement decorrelation.
文摘针对无迹卡尔曼滤波(unscented Kalman filter,UKF)算法估计锂电池荷电状态(state of charge,SOC)时精度低、稳定性差、产生的sigma点过多导致计算难度大等不足,提出一种基于自适应球形不敏变换方式的无迹卡尔曼滤波(unscented Kalman filter based on adaptive spherical insensitive transformation,ASIT-UKF)算法。该算法通过使用球形不敏变换方式选择权系数以及初始化一元向量对sigma点的产生进行选取。与UKF算法相比,ASIT-UKF算法产生的sigma点减少近50%,使得算法的计算复杂度大大降低。同时,将产生的所有sigma点进行单位球形面上的归一化处理,提高了数值的稳定性。考虑到实际运行中锂电池系统噪声干扰带来的不确定性,加入Sage-Husa自适应滤波器对不确定性噪声的干扰进行实时更新和修正,以达到提高在线锂电池SOC估计精度的目的。最后,将均方根误差和最大绝对误差计算公式引入到性能估计指标中。实验结果表明,ASIT-UKF算法在准确度、鲁棒性和收敛性方面具有优越的性能。
文摘动态电压恢复器(dynamic voltage restorer,DVR)的响应速度是衡量DVR特性的重要指标,锁相环和电压跌落检测算法则是决定其响应速度的2个关键因素,而电网电压畸变、跌落过程中发生的相位跳变和电压不平衡制约着锁相环和检测算法的快速性。该文结合最小方差(least error squares,LES)滤波器和改进对称分量法设计了新的软件锁相环和电压跌落检测算法,对这2种方法进行详细的理论推导,阐明各频次的正负序分量解耦的机理。在Matlab/Simulink中搭建仿真模型,与传统锁相环方法和电压跌落检测算法进行对比分析。最后,在电压跌落平台进行工业样机验证,结果表明所提方法可行有效,且具有较高的响应速度。
基金国家自然科学基金(the National Natural Science Foundation of China under Grant No.60475007)国家高技术研究发展计划(863)(the National High-Tech Research and Development Plan of China under Grant No.2006AA010102)。
