线性分式扰动下奇异系统鲁棒滤波递推算法

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....

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Published inZi dong hua xue bao Vol. 33; no. 11; pp. 1150 - 1155
Main Author 张光磊 周彤
Format Journal Article
LanguageChinese
Published 清华大学自动化系,北京,100084 2007
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ISSN0254-4156
1874-1029

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Abstract 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.
AbstractList TP13; 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.
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.
Author 张光磊 周彤
AuthorAffiliation 清华大学自动化系,北京100084
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ZHOU Tong
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Keywords Kalman滤波
奇异系统
鲁棒性
线性分式不确定性
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Snippet 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...
TP13; 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...
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SubjectTerms Kalman滤波
奇异系统
线性分式不确定性
鲁棒性
Title 线性分式扰动下奇异系统鲁棒滤波递推算法
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