Discrete-time networked control systems under stochastic scheduling constraints

Kun Liu, Xia Pan, Yang Liu, Yuanqing Xia

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

This paper extends the time-delay approach to discrete-time networked control systems with multiple sensor nodes that are subject to time-varying transmission intervals, time-varying transmission delays and communication constraints. The system sensor nodes are supposed to be distributed over a network. The scheduling of sensor communication is ruled by an independent and identically-distributed stochastic process. The activation probability of each sensor node is a given constant, whereas it is assumed that collisions occur with a certain probability. The closed-loop system is modelled as a discrete-time stochastic hybrid system with time-varying delays in the dynamics and in the reset conditions. By Lyapunov method a new condition is derived for the exponential mean-square stability of the delayed hybrid systems with respect to the full state and not only to the partial state. The communication delays are allowed to be greater than the sampling intervals. The efficiency of the proposed method is illustrated on the example of cart-pendulum.

Original languageEnglish
Title of host publicationProceedings of the 35th Chinese Control Conference, CCC 2016
EditorsJie Chen, Qianchuan Zhao, Jie Chen
PublisherIEEE Computer Society
Pages7369-7374
Number of pages6
ISBN (Electronic)9789881563910
DOIs
Publication statusPublished - 26 Aug 2016
Event35th Chinese Control Conference, CCC 2016 - Chengdu, China
Duration: 27 Jul 201629 Jul 2016

Publication series

NameChinese Control Conference, CCC
Volume2016-August
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference35th Chinese Control Conference, CCC 2016
Country/TerritoryChina
CityChengdu
Period27/07/1629/07/16

Keywords

  • Discrete-time networked control
  • Lyapunov method
  • large communication delays
  • multiple sensors
  • stochastic protocol

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