广义2-D Roesser模型的状态滤波器  

State Filter of Singular 2-D Roesser Models

作　　者：盛梅[1] 邹云[2] 

机构地区：[1]南京理工大学应用数学系,江苏南京210094 [2]南京理工大学自动化院,江苏南京210094

出　　处：《兵工学报》2006年第3期432-436,共5页Acta Armamentarii

基　　金：国家自然科学基金资助项目(60474078;60304001;60574015);南京理工大学科研启动基金(XKL20051024)

摘　　要：研究了状态和测量同时受白噪声干扰时广义随机2-D Roesser模型的状态滤波器设计问题。将Kalman滤波器的设计推广至广义2-D Roesser模型。通过逐行扫描法,模能重构的广义2-D Roesser模型的滤波问题得到了解决,获得了状态向量的最优滤波的计算公式。计算步骤和例子说明了设计的滤波器的有效性。The problem of state estimator design for stochastic singular 2-D Roesser models subjected to white noises in both the state and measurement equations was studied. The well-known Kalman filter design was extended to singular 2-D Roesser models that minimizes the variance of the estimation error of state vectors. The filtering problem of jump-mode reconstructable singular 2-D Roesser models was solved through the method of ＂scanning row by row＂. Explicit formulas of the estimator was derived and based on which a numerical procedure was proposed to demonstrate the validity of the designed filter.

关 键 词：控制理论 广义系统 2-D系统 ROESSER模型 KALMAN滤波器 

分 类 号：TP271.8[自动化与计算机技术—检测技术与自动化装置]