Consensus control of networked multi-agent systems based on a novel hybrid transmission strategy

He, Junda; Zhou, Chuan; Wang, Tengli; Guo, Jian

doi:10.1093/imamci/dnx027

Cited by 3 publications

(1 citation statement)

References 19 publications

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“…In recent years, cooperative control of multiagent systems has been a hot research area, where the collective missions can be completed by interconnected communication. Consensus is the central problem in the study of cooperative control due to the wide applications in real‐engineering applications including formation control, 1‐3 flocking behavior, 4‐7 and sensor networks 8 . A series of results about the consensus of multiagent systems with distinct dynamics are proposed such as second‐order dynamics, 9‐12 general linear dynamics, 13 and nonlinear dynamics 14,15 .…”

Section: Introductionmentioning

confidence: 99%

Randomized optimal consensus of multiagent systems based on a novel intermittent projected subgradient algorithm

Shi

Zhou

2020

Optim Control Appl Methods

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Summary In this article, a novel intermittent projected subgradient algorithm is presented to solve the randomized optimal consensus problem for heterogeneous multiagent systems with time‐varying communication topologies. The multiagent systems achieve the consensus meanwhile minimizing the global objective function ∑i=1mfi(x) via the proposed algorithm, where fi(x) is the convex objective function of agent i itself. Due to the common Bernoulli distribution adopted in the existing random optimization algorithm without considering the different computing capability of each agent. An individual projection probability is assigned for each agent based on computing capabilities so that either making projection or taking average is chosen according to the above probability which can effectively avoid overload for some agents with lower computing capabilities and improve the reliability of the overall systems. A new sufficient step‐size condition is given to ensure all agents converge to the optimal solution with probability one. Finally, a numerical example is also given to validate the proposed method.

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Section: Introductionmentioning

confidence: 99%

Randomized optimal consensus of multiagent systems based on a novel intermittent projected subgradient algorithm

Shi

Zhou

2020

Optim Control Appl Methods

Self Cite

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Cooperative optimal control for descriptor multi-agent systems

Zhang

2019

IMA Journal of Mathematical Control and Information

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This paper provides a theory analysis of cooperative optimal control problem for leader-follower descriptor multi-agent systems. Based on the linear quadratic regulator theory, the state feedback controller is designed to guarantee the consensus of multi-agent systems and minimize a local performance index, which is independent of the graph topology, the control gain matrix is obtained by solving a generalized Riccati equation. Because the local optimal protocol devised cannot guarantee the global optimality of the entire system, the inverse optimal control theory is applied to design distributed control protocols that ensure consensus and global optimality with respect to some global performance index. The defined performance index is related to the interaction topology, whose Laplacian matrix is constrained to be diagonalizable. Finally, two numerical examples and comparisons are supplied to verify the effectiveness of the theoretical results.

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Networked Evolutionary Game Analysis on Strategy Consensus Under Pinning Control Based on Degree

Jiang,

Yu,

Yan

et al. 2024

2024 9th International Conference on Automation, Control and Robotics Engineering (CACRE)

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Consensus control of networked multi-agent systems based on a novel hybrid transmission strategy

Cited by 3 publications

References 19 publications

Randomized optimal consensus of multiagent systems based on a novel intermittent projected subgradient algorithm

Randomized optimal consensus of multiagent systems based on a novel intermittent projected subgradient algorithm

Cooperative optimal control for descriptor multi-agent systems

Networked Evolutionary Game Analysis on Strategy Consensus Under Pinning Control Based on Degree

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