Model-based networked control system stability based on packet drop distributions

Teng, Lanzhi and Wen, Peng and Xiang, Wei (2008) Model-based networked control system stability based on packet drop distributions. In: 10th International Conference on Control, Automation, Robotics and Vision (ICARCV 2008), 17-20 Dec 2008, Hanoi, Vietnam.

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Abstract

This paper studies the system stability of a Model-Based Networked Control System in the cases where packet losses follow a certain distributions. In this study, the unreliable nature of network links is modelled as a stochastic process. This process provides us two system structures, representing packets dropped and received respectively. This new system with two structures is asymptotically stable, if the plant model is updated with the data from plant within the maximum interval and the packet drop follows discrete distributions with finite expectations such as Uniform Distribution and Bernoulli distribution. If the packet loss follows discrete distributions with infinite expectation such as Poissonian Distribution, the stochastic system is stable when the biggest interval is limited to the maximal update time interval. These results are verified in simulations.

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Item Type:	Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed:	Yes
Item Status:	Live Archive
Additional Information:	© 2008 IEEE. Permanent restricted access to published version due to publisher copyright policy. Author's version deposited in accordance with the copyright policy of the publisher.
Faculty / Department / School:	Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering
Date Deposited:	16 Feb 2009 11:42
Last Modified:	25 Nov 2014 02:04
Uncontrolled Keywords:	packet drop distribution; model-based networked control system; system stability
Fields of Research :	01 Mathematical Sciences > 0104 Statistics > 010406 Stochastic Analysis and Modelling 10 Technology > 1005 Communications Technologies > 100503 Computer Communications Networks 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080110 Simulation and Modelling
Socio-Economic Objective:	E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI:	10.1109/ICARCV.2008.4795567
URI:	http://eprints.usq.edu.au/id/eprint/4856

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