Distributed event-triggered scheduling in networked interconnected systems with sparse connections

Yanpeng Guan, Guonan Ping, Wei Xing Zheng, Huijuan Yao

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

This paper is concerned with the problem of distributed event-triggered scheduling for a class of interconnected systems with limited coupling connections. Different from the existing studies, in the considered interconnected system, each remote control station is allowed to retrieve event-triggered sampled-data from interacting control stations, while the number of coupling communication connections is upper bounded in a κ-sparse sense rather than permanently fixed. The distributed event-triggered scheduling problem subject to such a cardinality constraint is nontrivial due to its combinatorial nature. Different from the existing l1 norm based iterative convexification approach, a direct design approach based on mixed-integer programming is proposed to handle the cardinality constraint. Furthermore, an explicit κ-sparse distributed scheduling algorithm is designed for the networked interconnected system via the Lyapunov functional method and some matrix manipulations. The proposed approach is finally applied to a three-machine power system to illustrate its effectiveness.
Original languageEnglish
Pages (from-to)420-428
Number of pages9
JournalNeurocomputing
Volume400
DOIs
Publication statusPublished - 2020

Keywords

  • Lyapunov functions
  • algorithms
  • event processing (computer science)
  • interconnected systems
  • neural networks (computer science)
  • sparse matrices

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