Paper Info
Title
Mean Square Stability Of Linear Systems With Poisson Jumps
Abstract
This paper deals with the class of linear systems subject to Poisson jumps, where the dwel-ltime between jumps is described by an exponential distribution with mode-dependent parameter. No probabilistic information on the sequence of modes is assumed available. This model can be viewed as an uncertain Markov Jump Linear System (MJLS) with a transition rate matrix belonging to a polytope. Thanks to this interpretation, we show that mean square stability is equivalent to stability under arbitrary switching of a deterministic system. This allows one to derive sufficient conditions for mean square stability based on common Lyapunov functions, easily testable via semidefinite programming. Conservatism of the proposed conditions is discussed along with the relative implications among them.
Year
Venue
Keywords
2017
2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC)
Poisson jumps, Switched systems, Markov Jump Linear Systems, Mean square stability
Field
DocType
ISSN
Applied mathematics,Lyapunov function,Linear system,Computer science,Control theory,Markov chain,Exponential stability,Exponential distribution,Deterministic system,Poisson distribution,Semidefinite programming
Conference
0743-1546
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Paolo Bolzern130430.90
Patrizio Colaneri295090.11