【作者】 卢晓； 张焕水； 王伟；

【Author】 LuXiao, Zhang Huanshui, Wang Wei (Dalian University of Science and Technology, Dalian ,116023;) (Shenzhen Graduate School of Harbin Institute of Technology, Shenzhen ,518055)

【机构】 大连理工大学自动化系； 哈尔滨工业大学深圳研究生院航天学院；

【摘要】 本文研究具有即时观测和两个延迟观测系统的线性最小均方差估计。利用新息重组理论提出了一种简便有效的算法,问题归结为计算三个与原系统有相同维数的标准Kalman滤波器。与传统的状态增广方法相比较,计算得到大大简化,其关键技术是由我们定义的重组新息。本文提出的理论方法具有很大的推广应用价值,可用来解决控制理论中一些疑难问题如H无穷固定时滞平滑估计及时滞系统和控制等。更多还原

【Abstract】 This paper is to study the linear minimum variance estimation for discrete-time systems with instantaneous and two time delayed measurements. A simple approach to the problem is presented by developing re-organized innovation analysis. It is shown that the derived estimator involves solving three different standard Kalman filtering with the same dimension as the original system. The approach is shown to induce significant saving of computational cost as compared to the system augmentation approach, the key technology is re-organized innovation analysis. The obtained results form the basis for solving some complicated problems such as H∞ fixed-lag smoothing, preview control, H∞filtering and control with time delays.更多还原