| 引用本文: | 许波,朱熀秋,姬伟,潘伟,孙晓东.改进型平方根无迹卡尔曼滤波及其在无轴承永磁同步电机无速度传感器运行中的应用[J].控制理论与应用,2012,29(1):53~58.[点击复制] |
| XU Bo,ZHU Huang-qiu,JI Wei,PAN Wei,SUN Xiao-dong.Modified square-root unscented Kalman filter and its application to speed sensorless control of bearingless permanent magnet synchronous motor[J].Control Theory and Technology,2012,29(1):53~58.[点击复制] |
|
| 改进型平方根无迹卡尔曼滤波及其在无轴承永磁同步电机无速度传感器运行中的应用 |
| Modified square-root unscented Kalman filter and its application to speed sensorless control of bearingless permanent magnet synchronous motor |
| 摘要点击 2648 全文点击 2111 投稿时间：2010-12-20 修订日期：2011-03-14 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| DOI编号 10.7641/j.issn.1000-8152.2012.1.CCTA101461 |
| 2012,29(1):53-58 |
| 中文关键词 平方根无迹卡尔曼滤波(SRUKF) 改进SRUKF 无轴承永磁同步电机 无速度传感器 |
| 英文关键词 square root unscented Kalman filter (SRUKF) modified SRUKF bearingless permanent magnet synchronous motor (BPMSM) speed sensorless |
| 基金项目 国家自然科学基金资助项目(50275067); 国家高技术研究发展计划资助项目(2007AA04Z213); 江苏省2009年度普通高校研究生科研创新计划基金资助项目(CX09B-200Z); 江苏省高校优势学科建设工程资助项目(PAPD, 苏政办发(2011)6号). |
|
| 中文摘要 |
| 平方根无迹卡尔曼滤波(SRUKF)解决了标准无迹卡尔曼滤波(UKF)中由于误差协方差阵负定而引起的滤波发散问题, 保证了算法的数值稳定性, 但仍存在对模型参数变化的鲁棒性差、收敛速度慢及对突变状态的跟踪能力低等缺陷. 因此, 本文提出一种改进SRUKF滤波, 通过引入时变渐消因子和弱化因子, 实时修正滤波增益矩阵和误差协方差平方根矩阵, 实现残差序列正交, 确保SRUKF滤波保持对目标实际状态的准确跟踪. 将该算法在无轴承永磁同步电机无速度传感器矢量控制系统中进行仿真研究. 结果表明: 改进SRUKF非线性近似精度、数值稳定性及滤波精度更高, 在系统状态突变或负载扰动时, 鲁棒性更强, 能够有效实现转速及转子角度的准确估计, 确保转子稳定悬浮运行. |
| 英文摘要 |
| The square-root unscented Kalman filter (SRUKF) algorithm handles the problem of filtering divergence caused by non-positiveness of the error covariance matrix in conventional unscented Kalman filter (UKF). However, problems of low robustness to model parameter variation, slow convergence, and undesirable tracking ability to abrupt statechanges remain unsolved. We propose an improved SRUKF by introducing the time-varying fading factor and the diminishing factor to adjust gain matrices and the state-forecast covariance square-root matrix, in order to realize the orthogonality of the residual sequences and force the SRUKF to track the real-state rapidly. The vector control system for the bearingless permanent magnet synchronous motor (BPMSM) without a speed sensor is set up based on this approach. Simulation results show that the proposed method improves the nonlinear approximation accuracy and raises numerical stability and filtering efficiency; it achieves high robustness to the abrupt state-changes and the load disturbances; it provides precise estimates of the speed and the space position, and ensures the stable operation of the rotor suspension. |
|
|
|
|
|