Containment control of hybrid multi‐agent systems

Chen, Yarui; Zhao, Qi; Zheng, Yufan; Zhu, Yunru

doi:10.1002/rnc.5883

Cited by 11 publications

(6 citation statements)

References 34 publications

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“…Among them γ M = max {γ i |i = 1, 2, ......, N }, λ n indicates the largest eigenvalue of the Laplacian matrix L. By substituting all the above inequalities into (14), the above formula becomes…”

Section: Resultsmentioning

confidence: 99%

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Group Consensus of Hybrid Multi-Agent Systems With Event-Triggering Conditions

Pei,

Zhou,

Tan

2023

IEEE Access

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This paper investigates the group consensus problem of hybrid multi-agent systems(HMASs) under event-triggering conditions. The communication between multi-agents can be effectively reduced by the event-triggering mechanism, and the energy consumption of system can be saved. First, a HMAS is constructed, which composes of individuals with continuous and discrete two states. A distributed hybrid multi-agent group consensus controller is proposed. Then considering the joint measurement method, appropriate event-triggering strategy is given, which effectively avoids the occurrence of Zeno phenomenon. Lyapunov's method is used to prove that system can finally achieve group consensus. Finally, the correctness of the research results is confirmed by simulation.INDEX TERMS HMASs; event-triggering condition; group consensus.

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Section: Resultsmentioning

confidence: 99%

“…In [13], two different HMAS models were explored, and the system consensus problem was solved. For hybrid systems, a new control protocol based on the containment control method was proposed in [14]. In summary, the control method of HMAS is more flexible.…”

Section: Introductionmentioning

confidence: 99%

Group Consensus of Hybrid Multi-Agent Systems With Event-Triggering Conditions

Pei,

Zhou,

Tan

2023

IEEE Access

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“…The authors in Reference 18 studied the uncertain heterogeneous MASs, and model reference adaptive controllers were introduced. Recently, containment control of stochastic MASs, 19 fractional‐order MASs, 20 hybrid MASs, 21 and partial differential equations MASs 22 have also been studied.…”

Section: Introductionmentioning

confidence: 99%

Optimal containment control for a class of heterogeneous multi‐agent systems with actuator faults

Fan,

Wang,

et al. 2023

Intl J Robust & Nonlinear

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This article investigates the optimal containment control problem for a class of heterogeneous multi‐agent systems with time‐varying actuator faults and unmatched disturbances based on adaptive dynamic programming. Since there exist unknown input signals in each leader, distributed observers are utilized to estimate trajectories in the convex hull spanned by leaders. The containment control problem is then transformed into an optimal tracking problem. To compensate for the actuator faults and unmatched disturbances, a novel performance index function is designed. We prove that the optimal control policy can ensure that the tracking error system of each follower is uniformly ultimately bounded. The online policy iteration algorithm is implemented using critic neural networks to obtain the optimal control policy. A numerical example is provided to demonstrate the effectiveness of the proposed control policy.

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“…In this paper, the agents are divided into three types according to their respective missions, that is, a tracking-leader (as the capable leader to provide the desired move trajectory), 39 formation-leaders (equipped with sensors to detect dangerous obstacles, forming a safety area or organizing an expected formation configuration) and followers (staying within the safety area spanned by formation-leaders). 22,[40][41][42][43][44][45][46] Obviously, the consensus problem, formation problem and containment problem can be treated as the special case of formation-containment control problems.…”

Section: Introductionmentioning

confidence: 99%

Appointed‐time formation‐containment control for nonlinear multi‐agent networks using sample‐data feedback

Zhou

Liu

Zhao

et al. 2023

Intl J Robust & Nonlinear

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This paper focuses on the single-and second-order nonlinear multi-agent systems, contributing to realizing the formation-containment control over directed communication networks, respectively. By dividing the agents into three types, that is, the tracking-leader, formation-leaders and followers, a class of two-layer sample-data formation-containment control protocols are developed. Then, under the proposed sample mechanism, the investigated problem is transformed into a motion planning problem and the influence caused by non-identical nonlinear dynamics is offset by integral techniques. It shows that with the time projection method, the formation-containment behaviour emerges at an appointed time, which is regardless of any parameters and initial conditions for agents. In comparison with previous results, the main contribution of this paper is achieving the appointed-time formation-containment control and appointed-time tracking to a dynamic leader with nonlinear dynamics. Moreover, the condition on dynamics is more relaxed, only requiring the nonlinearities errors to be bounded. Finally, two simulation examples are given to indicate the effectiveness of obtained results.

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Containment control of hybrid multi‐agent systems

Cited by 11 publications

References 34 publications

Group Consensus of Hybrid Multi-Agent Systems With Event-Triggering Conditions

Group Consensus of Hybrid Multi-Agent Systems With Event-Triggering Conditions

Optimal containment control for a class of heterogeneous multi‐agent systems with actuator faults

Appointed‐time formation‐containment control for nonlinear multi‐agent networks using sample‐data feedback

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