Distributed Model Predictive Consensus With Self-Triggered Mechanism in General Linear Multiagent Systems

Jingyuan Zhan, Zhong Ping Jiang, Yebin Wang, Xiang Li

Research output: Contribution to journalArticle

Abstract

This paper investigates the consensus problem of general linear discrete-time multiagent systems by using distributed model predictive control (DMPC) with self-triggered mechanism. First, a novel DMPC-based consensus algorithm is proposed, where each agent only needs to obtain its neighbors' predicted state sequences once at each time step. We prove that the resultant DMPC optimization problem is feasible, and the proposed algorithm guarantees the dynamic consensus of agents. Then, to further reduce the communication cost and the energy consumption of control updates, a self-triggered DMPC-based consensus algorithm is proposed with the control input and the triggering interval jointly optimized. Numerical examples including the benchmark problem with platooning vehicles are provided to verify the effectiveness and advantages of the proposed algorithms.

Original languageEnglish (US)
Article number8556099
Pages (from-to)3987-3997
Number of pages11
JournalIEEE Transactions on Industrial Informatics
Volume15
Issue number7
DOIs
StatePublished - Jul 2019

Keywords

  • Consensus
  • distributed model predictive control (DMPC)
  • multiagent system
  • self-triggered control

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Electrical and Electronic Engineering

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