Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 917-925 |
| Journal | Automatica |
| Volume | 48 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 2012 |
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Stability analysis of stochastic networked control systems. / Donkers, M.C.F.; Heemels, W.P.M.H.; Bernardini, D.; Bemporad, A.; Shneer, V.
In: Automatica, Vol. 48, No. 5, 2012, p. 917-925.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - Stability analysis of stochastic networked control systems
AU - Donkers, M.C.F.
AU - Heemels, W.P.M.H.
AU - Bernardini, D.
AU - Bemporad, A.
AU - Shneer, V.
PY - 2012
Y1 - 2012
N2 - In this paper, we study the stability of Networked Control Systems (NCSs) that are subject to time-varying transmission intervals, time-varying transmission delays, packet dropouts and communication constraints. The transmission intervals and transmission delays are described by a sequence of continuous random variables. The complexity that the continuous character of these random variables introduces is overcome using a novel convex overapproximation technique that preserves the available probabilistic information. By focusing on linear plants and controllers, we present a modelling framework for NCSs based on discrete-time linear switched and parameter-varying systems. Stability (in the mean-square) of these systems is analysed using a new stochastic computational technique, resulting in a finite number of linear matrix inequalities. We illustrate the developed theory on the benchmark example of a batch reactor.
AB - In this paper, we study the stability of Networked Control Systems (NCSs) that are subject to time-varying transmission intervals, time-varying transmission delays, packet dropouts and communication constraints. The transmission intervals and transmission delays are described by a sequence of continuous random variables. The complexity that the continuous character of these random variables introduces is overcome using a novel convex overapproximation technique that preserves the available probabilistic information. By focusing on linear plants and controllers, we present a modelling framework for NCSs based on discrete-time linear switched and parameter-varying systems. Stability (in the mean-square) of these systems is analysed using a new stochastic computational technique, resulting in a finite number of linear matrix inequalities. We illustrate the developed theory on the benchmark example of a batch reactor.
U2 - 10.1016/j.automatica.2012.02.029
DO - 10.1016/j.automatica.2012.02.029
M3 - Article
VL - 48
SP - 917
EP - 925
JO - Automatica
JF - Automatica
SN - 0005-1098
IS - 5
ER -