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Scheduling Algorithms of Flat Semi-Dormant Multicontrollers for a Cyber-Physical System

Recently, the modeling and design of distributed controllers in cyber-physical systems (CPSs), which suffer from messages lost, delay variation, and jitter, has gained lots of research attentions. A special CPS, arbitrated networked control system (ANCS), has been designed for scheduling or arbitrat...

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Bibliographic Details
Published in:IEEE transactions on industrial informatics 2017-08, Vol.13 (4), p.1665-1680
Main Authors: Gong, Hongfang, Li, Renfa, An, Jiyao, Chen, Weiwei, Li, Keqin
Format: Article
Language:English
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Summary:Recently, the modeling and design of distributed controllers in cyber-physical systems (CPSs), which suffer from messages lost, delay variation, and jitter, has gained lots of research attentions. A special CPS, arbitrated networked control system (ANCS), has been designed for scheduling or arbitrating networks in a control system. In this paper, we propose a novel ANCS with dual communication channels. The proposed ANCS uses a hierarchical flexible time-division multiple access (TDMA)/fixed priority scheduling policy that is based on the event trigger protocol. A flat semi-dormant multicontrollers (FSDMC) model is developed for the proposed ANCS. We then model the FSDMC as an N/(d,c)-M/M/c/K/SMWV queue, and obtain various performance indices. Based on the model, a multiobjective optimization problem is then formulated to minimize the nonlinear energy consumption function and the nominal delay function presented in this study. To resolve the multiobjective optimization problem, a scheduling algorithm based on the multiobjective particle swarm optimization algorithm is proposed to generate the Pareto front and the corresponding nondominated vector sets. An optimal stopping algorithm is also designed to obtain the optimal value of the number of semi-dormant controllers. The optimal values of various parameters of the control system are obtained by using the above nondominated vector sets, and are applied to the proposed ANCS. Extensive numerical results are provided to illustrate the usefulness of the proposed algorithms and the effects of the control system parameters on the optimal policy.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2017.2690939