Distributed Dynamic Event-Based Control for Nonlinear Multi-Agent Systems

Tan, Xuegang; Cao, Ming; Cao, Jinde

doi:10.1109/tcsii.2020.3006125

Cited by 14 publications

(17 citation statements)

References 18 publications

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“…As the number of nodes increases, the computation load of the MASs under these methods will increase. Different from the schemes in [11], [12], and [20], a method estimating the lower bound of the second smallest eigenvalue associated with the Laplacian matrix is introduced to solve the synchronization problem of MASs [32]- [34]. Although the strategy proposed in [32]- [34] requires that each agent obtains the total agent number, it reduces skillfully the dimension of matrix inequality in the synchronization criteria.…”

Section: Event-triggered Synchronization Of Multiagentmentioning

confidence: 99%

Event-Triggered Synchronization of Multiagent Systems With Partial Input Saturation

Tan

Cao

et al. 2021

IEEE Trans. Control Netw. Syst.

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This article is concerned with the distributed event/self-triggered synchronization problem for general linear multiagent systems with partial input saturation. Both the event-based and self-triggered laws are designed using the local sampled, possibly saturated, state, which ensures the bounded synchronization of the multiagent systems and exclusion of the Zeno-behavior. The continuous communication between agents is avoided under these triggering protocols. Different from the existing related works, we show the fully distributed design for multiagent systems, where the synchronization criteria, the designed input laws, and the proposed triggering protocols do not depend on any global information of the communication topology. In addition, the computational load of multiagent systems is reduced significantly.

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Section: Event-triggered Synchronization Of Multiagentmentioning

confidence: 99%

Event-Triggered Synchronization of Multiagent Systems With Partial Input Saturation

Tan

Cao

et al. 2021

IEEE Trans. Control Netw. Syst.

Self Cite

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“…In recent years, many important results have been obtained on consensus of MASs, whose goal is to enable agents to perform a designated task synchronously [11], [12]. Tian et al proposed output consensus for second-order MASs [13].…”

Section: Introductionmentioning

confidence: 99%

Leaderless Consensus Control of Nonlinear PIDE-Type Multi-Agent Systems With Time Delays

Dai

Yang

et al. 2022

IEEE Access

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This paper studies leaderless consensus of semi-linear parabolic partial integro-differential equations based multi-agent systems (PIDEMASs) with time delays. Making use of the information interaction and coordination among the neighboring agents, consensus control of the leaderless PIDEMAS is constructed. Consensus of the leaderless PIDEMAS is analyzed by using a Lyapunov approach. Dealing with time-invariant delays and time-varying delays, two sufficient conditions for consensus of the leaderless PIDEMAS are respectively obtained in terms of LMIs. Two examples illustrate the effectiveness of developed theoretical results.INDEX TERMS consensus, multi-agent systems, LMIs, Lyapunov, partial integro-differential equations.

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“…E Vent-triggered control, whose basic idea is to replace the continuous or periodic sampling mechanism by the aperiodic and sporadic one in the control algorithms [1], [2], [3], [4], [5], [6], originates form the aperiodic sampling problem [7] and shows great effectivity when applied in controlling continuous-time systems with digital controllers. In the last decade or so, it has been further introduced to distributed control of network systems [8], [9], [10], [11], [12], [13], [14], wherein not only the sampling mechanism but also the communicating mechanism among agents is event-based.…”

Section: Introductionmentioning

confidence: 99%

“…Reference [44] introduced the event-triggered mechanism to dynamic average consensus (DAC) algorithms. [11], [13], [14], [39], [40], [41] considered the event-triggered leader-following tracking problems and [12] further considered distributed dynamic event-triggered control for nonlinear multi-agent systems.…”

Section: Introductionmentioning

confidence: 99%

An Operator-Theoretic Approach to Robust Event-Triggered Control of Network Systems with Frequency-Domain Uncertainties

Zhang¹,

Li²

2022

Preprint

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In this paper, we study the robustness of the event-triggered consensus algorithms against frequencydomain uncertainties. It is revealed that the sampling errors resulted by event triggering are essentially images of linear finite-gain L 2 -stable operators acting on the consensus errors of the sampled states and the event-triggered mechanism is equivalent to a negative feedback loop introduced additionally to the feedback system. In virtue of this, the robust consensus problem of the event-triggered network systems subject to additive dynamic uncertainties and network multiplicative uncertainties are considered, respectively. In both cases, quantitative relationships among the parameters of the controllers, the Laplacian matrix of the network topology, and the robustness against aperiodic event triggering and frequency-domain uncertainties are unveiled. Furthermore, the event-triggered dynamic average consensus (DAC) problem is also investigated, wherein the sampling errors are shown to be images of nonlinear finite-gain operators. The robust performance of the proposed DAC algorithm is analyzed, which indicates that the robustness and the performance are negatively related to the eigenratio of the Laplacian matrix. Simulation examples are also provided to verify the obtained results.

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Distributed Dynamic Event-Based Control for Nonlinear Multi-Agent Systems

Cited by 14 publications

References 18 publications

Event-Triggered Synchronization of Multiagent Systems With Partial Input Saturation

Event-Triggered Synchronization of Multiagent Systems With Partial Input Saturation

Leaderless Consensus Control of Nonlinear PIDE-Type Multi-Agent Systems With Time Delays

An Operator-Theoretic Approach to Robust Event-Triggered Control of Network Systems with Frequency-Domain Uncertainties

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