线性分式扰动下奇异系统鲁棒滤波递推算法  

A Recursive Robust Filtering Algorithm for Descriptor Systems Subject to Linear Fractional Uncertainties

作　　者：张光磊[1] 周彤[1] 

机构地区：[1]清华大学自动化系,北京100084

出　　处：《自动化学报》2007年第11期1150-1155,共6页Acta Automatica Sinica

基　　金：国家自然科学基金(60574008;60625305);教育部博士点基金(20050003096)资助~~

摘　　要：研究了线性分式扰动下线性奇异系统的状态估计问题,给出了一种Kalman形式的递推滤波算法.研究表明,线性分式不确定性可以表示为一系列加性不确定性的交集.本文讨论了如何寻找保守性最弱的加性不确定性来近似该交集,并证明了该问题在鲁棒滤波过程中可以转化为凸优化问题.数值仿真验证了上述算法的有效性.对于具有结构约束的线性分式不确定性,该算法的性能优于现有算法.This paper deals with a robust state estimation problem of descriptor systems subject to linear fractional disturbances, and proposes a Kaiman type recursive filtering algorithm. It is proved that the linear fractional uncertainties can be equivalently represented by the intersection of a series of additive uncertainties. The problem of finding the least conservative set of additive uncertainties to approximate this intersection can be converted to a convex optimization one in the process of robust filtering. Numerical simulation results have also been reported which confirm the efficiency of the proposed algorithm. Moreover, for structured linear fractional uncertainties, the algorithm is shown to perform better than the available one.

关 键 词：KALMAN滤波 奇异系统 线性分式不确定性 鲁棒性 

分 类 号：TN713[电子电信—电路与系统]