Open AccessControl with sensors/actuators assigned by Markov chains: transition rates partially unknown
Author(s) -
Lu Zibao,
Guo Ge
Publication year - 2013
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2012.0879
Subject(s) - markov chain , control theory (sociology) , infinitesimal , actuator , markov process , transition rate matrix , mathematics , markov kernel , computer science , markov model , control (management) , variable order markov model , mathematical analysis , statistics , artificial intelligence
This study investigates systems where the sensors and the actuators are driven by two independent random events so that at any time only a subset of them is activated. The triggering events are modelled by two Markov chains with partially unknown transition rates. The authors derive a systematic control analysis and synthesis framework using theories in Markovian jumping systems and time‐delay systems. The results are given in terms of the delay bounds and the transition probabilities of the Markov chains, which are obtained by using a newly defined Lyapunov–Krasovskii functional and the weak infinitesimal operator. A numerical example is given to demonstrate the effectiveness of the proposed method.