A distributed event-triggered transmission strategy for sampled-data consensus of multi-agent systems

By Ge Guo, Lei Ding, Qing-Long Han. at - Automatisierungstechnik, 2014

664 citations recorded by the source corpus.

Abstract This paper is concerned with event-triggered sampled-data consensus for distributed multi-agent systems with directed graph. A novel distributed event-triggered sampled-data transmission strategy is proposed, which allows the event-triggering condition to be intermittently examined at constant sampling instants. Based on this novel strategy, a sampled-data consensus control protocol is presented, with which the consensus of distributed multi-agent systems can be transformed into the stability of a system with a time-varying delay. Then, a sufficient condition on the consensus of the multi-agent system is derived. Correspondingly, a co-design algorithm for obtaining both the parameters of the distributed event-triggered transmission strategy and the consensus controller gain is proposed. Two numerical examples are given to show the effectiveness of the proposed method.

Subfields: Computer Networks and Communications, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/2767d530bd9b99f31359fbdca7751b9ae33e1c7d

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In Computer Networks and Communications

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Citations in the corpus

Event-Based Finite-Time Control for Nonlinear Multiagent Systems With Asymptotic Tracking (2023, background): “First, only bounded error tracking could be given in the aforementioned results, and zero-error tracking could not be achieved in [2], [25], [26], [27], [28], [29], [30], [31].”
Event-Triggered Consensus Control for Multi-Agent Systems Against False Data-Injection Attacks (2019, background): “Different from [27], the advantages of the distributed event-triggered control strategy with state-dependent threshold for MASs have been studied in [28].”
Event-triggered communication and control of networked systems for multi-agent consensus (2017, methodology): “The event-triggered consensus of linear systems using ZOH implementations was also addressed in Guo, Ding, and Han (2014).”
Adaptive Consensus Control of Linear Multiagent Systems With Dynamic Event-Triggered Strategies (2020, background): “On the other hand, event-triggered control of MASs based on sampled data was addressed in [33]–[36], in which the triggering conditions were only judged at the sampling instants, which obviously avoided Zeno behavior.”
An Overview of Recent Advances in Event-Triggered Consensus of Multiagent Systems (2018, neutral): “For linear MASs with a directed graph containing a spanning tree, the sampled-data-based event-triggered consensus problem is dealt with in [60], where the ETC is set as ei (kh) ei(kh) ≤ σiẑi (kh) ẑi(kh) with σi > 0 being a threshold parameter and > 0 being a weighting matrix.”
Distributed Event-Triggered Scheme for Economic Dispatch in Smart Grids (2016, background): “for sampled data control systems and the multiagent systems are investigated in [11], [12], and [13].”
Fully Distributed Event-Triggered Protocols for Linear Multiagent Networks (2018, background): “In particular, several state feedback and observer-based output feedback eventtriggered consensus protocols for linear multiagent networks are presented in [15]–[18] and [20], and the event-triggered leader–follower consensus problem for multiagent systems in the presence of a leader with fixed and ”
Event-Triggered Adaptive Tracking Control for Multiagent Systems With Unknown Disturbances (2020, background): “[22] proposed a novel distributed eventtriggered sampled-data transmission protocol for distributed multiagent systems under a directed graph.”
A Distributed Dynamic Event-Triggered Control Approach to Consensus of Linear Multiagent Systems With Directed Networks (2020, background): “3) It is proven by contradiction that, with the proposed event-triggered control protocol, Zeno behavior can be excluded for any agent, while it is not involved in [26] and [27].”
Survey on Recent Advances in Networked Control Systems (2016, background): “, L2 analysis and control design [42], tracking control [79], dynamic output feedback control [77] [78], H∞ filtering [80], and consensus of multiagent systems [81].”
Neural-Network-Based Event-Triggered Adaptive Control of Nonaffine Nonlinear Multiagent Systems With Dynamic Uncertainties (2020, background): “[16] designed a novel distributed event-triggered sampled-data transmission protocol for multiagent systems.”