Paper Info
Title
Non-fragile sampled-data stabilization analysis for linear systems with probabilistic time-varying delays
Abstract
This paper deals with the problem of non-fragile sampled-data stabilization analysis for a class of linear systems with probabilistic time-varying delays via new double integral inequality approach. Based on the auxiliary function-based integral inequality (AFBII) and with the help of some mathematical approaches, a new double integral inequality (NDII) is developed. Then, to demonstrate the merits of the proposed inequality, an appropriate Lyapunov–Krasovskii functional (LKF) is constructed with some augmented delay-dependent terms. By employing integral inequalities, an enhanced stability criterion for the concerned system model is derived in terms of linear matrix inequalities (LMIs). Finally, three benchmark illustrative examples are given to validate the effectiveness and advantages of the proposed results.
Year
DOI
Venue
2019
10.1016/j.jfranklin.2018.11.046
Journal of the Franklin Institute
Field
DocType
Volume
Stability criterion,Mathematical optimization,Linear system,Matrix (mathematics),Auxiliary function,Multiple integral,Probabilistic logic,System model,Mathematics
Journal
356
Issue
ISSN
Citations 
8
0016-0032
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
R. Samidurai127515.47
R. Sriraman2214.67