2005
DOI: 10.1007/s00034-005-0921-1
|View full text |Cite
|
Sign up to set email alerts
|

Robust H∞ Filtering for Uncertain Discrete Stochastic Systems with Time Delays

Abstract: This paper considers the problem of robust H ∞ filtering for uncertain discretetime stochastic systems with time-varying delays. The parameter uncertainties are assumed to be real time-varying norm-bounded in both the state and measurement equations. The problem to be addressed is the design of a stable filter that guarantees stochastic stability and a prescribed H ∞ performance level of the filtering error system for all admissible uncertainties and time delays. A sufficient condition for the existence of suc… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4

Citation Types

0
37
0

Year Published

2007
2007
2017
2017

Publication Types

Select...
7

Relationship

2
5

Authors

Journals

citations
Cited by 43 publications
(37 citation statements)
references
References 17 publications
(14 reference statements)
0
37
0
Order By: Relevance
“…In many physical, industrial and circuit systems, time delays occur due to the finite capability of information processing, data transmission among various parts of the systems and some essential simplification of the corresponding process models [9,27,29,37,39,49,[55][56][57]. The delaying effect is often detrimental to the performance, and even renders instability.…”
Section: Introductionmentioning
confidence: 99%
“…In many physical, industrial and circuit systems, time delays occur due to the finite capability of information processing, data transmission among various parts of the systems and some essential simplification of the corresponding process models [9,27,29,37,39,49,[55][56][57]. The delaying effect is often detrimental to the performance, and even renders instability.…”
Section: Introductionmentioning
confidence: 99%
“…The complete classification of the "general situation" cases (this means that there are no special assumptions on the structure of state and observation equations and the initial conditions), where the nonlinear finite-dimensional filter exists, is given in Yau (1994). There also exists an extensive bibliography on robust, in particular, H ∞ filtering for linear (Xu and Chen (2003), Mahmoud and Shi (2003) and Xu et al (2005)) and nonlinear (Xie et al (1996), Nguang and Fu (1996), Fridman and Shaked (1997), Shi (1998), Fleming and McEneaney (2001), Yaz and Yaz (2001), Xu and van Dooren (2002), Wang et al (2003), Gao and Wang (2004), Zhang et al (2005), Gao et al (2005), Zhang et al (2007), Gao and Chen (2007), Wang et al (2008), Wang et al (2009), Wei et al (2009) and Shen et al (2009)) stochas-tic systems. Apart form the "general situation," the mean-square finite-dimensional filters have been designed for certain classes of polynomial system states with Gaussian noises over linear observations (Basin (2008), Basin et al (2008) and Basin et al (2009)) and a few results related to nonlinear Poisson systems can be found in Lu et al (2001), Kolmanovsky and Maizenberg (2002a), Hannequin and Mas (2002), Kolmanovsky and Maizenberg (2002b), Zhang et al (2008a), Dupé et al (2008), Zhang et al (2008b), and Basin and Maldonado (2011).…”
Section: Introductionmentioning
confidence: 99%
“…The H ∞ filter design implies that the resulting closed-loop filtering system is robustly stable and achieves a prescribed level of attenuation from the disturbance input to the output estimation error in the L 2 /l 2 -norm. Numerous results on this subject have been reported for systems in the general situation, linear or nonlinear (see [23,25,27,45,47,62,65,66,71]). For the specific area of linear time-delay systems, the H ∞ filtering problem has also been extensively studied (see [12, 21, 22, 24, 25, 28, 29, 33, 35, 40, 43, 56, 57, 59, 61, 63-66, 69, 72, 74]).…”
Section: Introductionmentioning
confidence: 99%