Event-based consensus of multi-agent systems with general linear models

Zhu, Wei; Jiang, Zhong‐Ping; Feng, Gang

doi:10.1016/j.automatica.2013.11.023

Cited by 610 publications

(317 citation statements)

References 22 publications

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“…Different from the traditional discrete-time updating controllers, the eventtriggered controller updates are determined by certain events that are triggered depending on the nodes' behavior. Based on the seminal works (Å ström and Bernhardsson 2002;Å ström 2008), the event-triggered controllers have been adopted widely for control science and engineering applications (Wang and Lemmon 2011;Mazo and Tabuada 2011;Tabuada 2007;Dimarogonas et al 2012;Almeida et al 2014;Liuzza et al 2013;Adaldo et al 2014;Zhu et al 2014;Fan et al 2013;Li et al 2015;Gao et al 2014;Zhou et al 2015a). In Dimarogonas et al (2012), the authors studied the event-triggered consensus of multiagent systems with undirected communication topology.…”

Section: Introductionmentioning

confidence: 99%

Event-based exponential synchronization of complex networks

2016

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In this paper, we consider exponential synchronization of complex networks. The information diffusions between nodes are driven by properly defined events. By employing the M-matrix theory, algebraic graph theory and the Lyapunov method, two kinds of distributed eventtriggering laws are designed, which avoid continuous communications between nodes. Then, several criteria that ensure the event-based exponential synchronization are presented, and the exponential convergence rates are obtained as well. Furthermore, we prove that Zeno behavior of the event-triggering laws can be excluded before synchronization being achieved, that is, the lower bounds of inter-event times are strictly positive. Finally, a simulation example is provided to illustrate the effectiveness of theoretical analysis.

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Section: Introductionmentioning

confidence: 99%

Event-based exponential synchronization of complex networks

2016

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“…On the other hand, in order to prolong the life time of digital control circuits, an effective method is to reduce the triggering frequency of electronic components. Therefore, the event-triggered scheduling seems to be more suitable for the consensus control of multi-agent systems and, accordingly, the event-triggered consensus control has received particular research attention in the past few years leading to some preliminary results reported in [11,13,19]. Note that most papers have been concerned with the asymptotic consensus issues for the 1st or 2nd order multi-agent systems with a relative change triggering condition, see Table 1 for a brief summary.…”

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confidence: 99%

“…Controller parameters [7,11,17] Controller & trigger parameters [13,19] Compared with the time-triggered control scheme [2,3,15,16], the distinct feature of event-triggered control strategy is that the control input is updated only when certain specific event happens. Between updates of the controller inputs, the control signal remains unchanged, and an appropriately generated updating time would guarantee the stability and performance of the closed-loop system.…”

mentioning

confidence: 99%

“…The 1st or 2nd order systems [17] General systems [7] Triggering conditions Absolute change conditions [13] Relative change conditions [11,17] Performances Asymptotic consensus [7,11,17] Bounded consensus [13,19] Design parameters…”

mentioning

confidence: 99%

“…However, the corresponding results concerning outputfeedback control have been scattered in the literature for general multi-agent systems. The 1st or 2nd order systems [11,13] General systems [19] Stochastic systems…”

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Event-triggered consensus control for discrete-time stochastic multi-agent systems: The input-to-state stability in probability

et al. 2015

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This paper is concerned with the event-triggered consensus control problem for a class of discrete-time stochastic multi-agent systems with state-dependent noises. A novel definition of consensus in probability is proposed to better describe the dynamics of the consensus process of the addressed stochastic multi-agent systems. The measurement output available for the controller is not only from the individual agent but also from its neighboring ones according to the given topology. An event-triggered mechanism is adopted with hope to reduce the communication burden, where the control input on each agent is updated only when a certain triggering condition is violated. The purpose of the problem under consideration is to design both the output feedback controller and the threshold of the triggering condition such that the closed-loop system achieves the desired consensus in probability. First of all, a theoretical framework is established for analyzing the so-called input-to-state stability in probability (ISSiP) for general discrete-time nonlinear stochastic systems. Within such a theoretical framework, some sufficient conditions on event-triggered control protocol are derived under which the consensus in probability is reached. Furthermore, both the controller parameter and the triggering threshold are obtained in terms of the solution to certain matrix inequalities involving the topology information and the desired consensus probability. Finally, a simulation example is utilized to illustrate the usefulness of the proposed control protocol.

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An Overview of Cooperative and Consensus Control of Multiagent Systems

Davoodi

Gallehdari

Saboori

et al. 2016

Wiley Encyclopedia of Electrical and Electronics Engineering

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There has been a growing interest toward the development of networked unmanned autonomous systems that can operate without an extensive involvement of humans. The motivation for this focus can be traced to the emergence of applications where direct human intervention is not possible due to the environmental hazards, complexity of the tasks, or other restrictions. These networks can consist of a large number of dynamical systems (agents), such as unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and unmanned underwater vehicles (UUVs). These systems commonly include a number of sensors, actuators, and decisionmakers. Therefore, the network of these systems is a network of a large number of sensors and actuators or, as is known in the literature, a system of systems (SoS). In this work, we provide a brief overview of controlling these networks, their applications, and the solutions that are proposed for these problems in the literature. Specifically, this article overviews recent results and progress made on multiagent consensus by focusing on cooperative control and consensus (formation) control in the presence of communication, control implementation, and saturation constraints. In addition, we review the active areas of event‐triggered consensus control, network security and attacks on the agents, and networks and resilient consensus control strategies that are proposed to handle these challenges.

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Event-based consensus of multi-agent systems with general linear models

Cited by 610 publications

References 22 publications

Event-based exponential synchronization of complex networks

Event-based exponential synchronization of complex networks

Event-triggered consensus control for discrete-time stochastic multi-agent systems: The input-to-state stability in probability

An Overview of Cooperative and Consensus Control of Multiagent Systems

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