广义系统降阶极点配置Kalman平滑器  

Reduced-Order Pole-Assignment Kalman Smoother for Descriptor Systems

作　　者：石莹[1] 孟华[1] 孙书利[1] 邓自立[1] 

机构地区：[1]黑龙江大学自动化系,哈尔滨150080

出　　处：《科学技术与工程》2003年第6期525-527,共3页Science Technology and Engineering

基　　金：国家自然科学基金(69774019);黑龙江省自然科学基金(F01-15)

摘　　要：基于广义随机系统的奇异值分解典范形,应用Kalman滤波和白噪声估值器,提出了全局渐近稳定的降阶极点配置固定滞后Kalman平滑器,可明显减小计算负担,便于实时应用,一个仿真例子说明了其有效性。Based on a singular value decomposition canonical form of descriptor stochastic systems, applying the Kalman filtering and white noise estimator, a globally asymptotically stable reduced-order pole-assignment fixed-lag Kalman smoother is presented. It can obviously reduces the computational burden, and is suitable for real time applications. A simulation example shows its effectiveness.

关 键 词：广义随机系统 奇异值分解 降阶 极点配置 Kalrnan平滑器 白噪声估值器 KALMAN滤波 

分 类 号：O211.64[理学—概率论与数理统计]