Event-Triggered Consensus Control for Linear Multi-Agent Systems

Liang, Jingxian; Liu, Kaien; Ji, Zhijian; Wang, Xiaoyu

doi:10.1109/access.2019.2944946

Cited by 15 publications

(9 citation statements)

References 31 publications

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“…. ., which denotes the current sampling time instant for agent i. erefore, event condition (10) leads to e(nT) T e(nT) ≤ c max z(nT) T z(nT),…”

Section: Periodic Communicationmentioning

confidence: 99%

“…Theorem 1. Consider the multiagent system (1) with the distributed sampled-data controller (17) and event condition (10) associated with the sum of relative state errors (9) under the undirected connected graph. en, control objective (3) is achieved as long as the following constraints are satisfied:…”

Section: Periodic Communicationmentioning

confidence: 99%

“…Theorem 3. Consider the multiagent system (1) governed by the distributed controller (17) associated with event condition (10) with respect to the sum of relative state errors (9) or (33). en, the multiagent systems under switching graphs G reach an average consensus as long as the following sufficient conditions and Assumption 2 are satisfied:…”

Section: Assumptionmentioning

confidence: 99%

“…Numerous applications of multiagent systems in the engineering field have emerged, such as in formation control [3][4][5], axis alignment of satellites [6], collective search and rescue operations [7], wireless sensor networks [8], and smart grids [9]. Given these applications, prompt solutions for the distributed coordination of multiagent systems are crucial, and some research has produced good results, mainly with regard to consensus protocols [10][11][12][13][14][15][16][17][18][19], consensus tracking [20], containment control [21], distributed average tracking [22], distributed estimates, and optimization [23], among others. However, in most previous studies, continuous-time sampling, communication, and control update are often assumed for each agent in a distributed consensus protocol.…”

Section: Introductionmentioning

confidence: 99%

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Event-Based Sampled-Data Average Consensus

Gong

Liu

et al. 2020

Mathematical Problems in Engineering

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This study addresses one of the most essential distributed control problems in multiagent systems, called the average consensus issue, using a new event-triggered sampling control perspective. Although the continuous-time sampling for average consensus has provided good results currently, a systematic investigation into the continuous-time agent dynamics with sampled-data control inputs under an event-triggered mechanism is critically lacking. The problem considered in this paper can be formulated into an average consensus problem of hybrid systems. The method considers three types of control schemes, among which periodic sampling is integrant. The first scheme is a classical sampling controller reinvestigated through a lemma. The second scheme realizes aperiodic control update as well as periodic communication, while the third scheme achieves both aspects aperiodically. Corresponding sufficient conditions of the aforementioned three schemes are derived such that the asymptotic stability of systems is ensured by using algebraic graph theory, matrix analysis, and Lyapunov theory. The constraints for the allowed sampling period, event parameter, and maximum eigenvalue of graph Laplacian are explicitly derived. Moreover, the potential Zeno behavior of agents due to the sampling control theory is avoided. Thus, a digitally implementable technique is provided. Finally, some numerical examples are provided to verify the effectiveness of the proposed theoretical analysis.

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“…. ., which denotes the current sampling time instant for agent i. erefore, event condition (10) leads to e(nT) T e(nT) ≤ c max z(nT) T z(nT),…”

Section: Periodic Communicationmentioning

confidence: 99%

Section: Periodic Communicationmentioning

confidence: 99%

Section: Assumptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Event-Based Sampled-Data Average Consensus

Gong

Liu

et al. 2020

Mathematical Problems in Engineering

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“…In the past years, some results were reported for the consensus of multi-agent systems under switched topologies in, e.g., [14]- [20]. The event-triggered consensus of multi-agent systems was introduced in [21]- [23]. According to [24]- [26], consensus-based power dispatch in the smart grid is an important application of consensus computation by multi-agent systems.…”

Section: Introductionmentioning

confidence: 99%

Consensus of Second-Order Multi-Agent Systems Without a Spanning Tree: A Sequence-Based Topology-Dependent Method

Zheng

Zhang

et al. 2020

IEEE Access

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This paper investigates the consensus of second-order multi-agent systems under switched topologies. Previous studies indicate that a consensus cannot be reached if the topology is fixed and has no spanning tree, but it is possible to reach a consensus for the multi-agent systems under switched topologies even if every topology has no spanning tree. However, in this paper, we show that some second-order multi-agent systems cannot reach a consensus even if the union of the directed interaction graphs has a spanning tree, and even if the union has a spanning tree frequently enough. It is often complex to judge whether the second-order multi-agent systems can reach a consensus or not under switched topologies if every topology has no spanning tree. This paper proposes a sequence-based topology-dependent method to determine whether a consensus can be reached in this circumstance. Our results are supported by examples and counterexamples. INDEX TERMS consensus, multi-agent systems, spanning tree, switched topologies

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