Consensus of second-order multi-agent systems via impulsive control using sampled hetero-information

Ding, Li; Yu, Ping; Liu, Zhi‐Wei; Guan, Zhi‐Hong; Feng, Gang

doi:10.1016/j.automatica.2013.06.014

Cited by 48 publications

(27 citation statements)

References 20 publications

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“…Many researchers are especially interested in the dynamical behavior analysis of multiagent networks, including consensus, cooperation, and competition (e.g., see [18], [24] and references therein). In particular, the secondorder multi-agent networks have brought much interest and their dynamic behaviors have been investigated widely [7], [19], [30].…”

Section: Introductionmentioning

confidence: 99%

A Second-Order Multi-Agent Network for Bound-Constrained Distributed Optimization

Liu

Wang

2015

IEEE Trans. Automat. Contr.

321

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This technical note presents a second-order multi-agent network for distributed optimization with a sum of convex objective functions subject to bound constraints. In the multi-agent network, the agents connect each others locally as an undirected graph and know only their own objectives and constraints. The multi-agent network is proved to be able to reach consensus to the optimal solution under mild assumptions. Moreover, the consensus of the multi-agent network is converted to the convergence of a dynamical system, which is proved using the Lyapunov method. Compared with existing multi-agent networks for optimization, the second-order multi-agent network herein is capable of solving more general constrained distributed optimization problems. Simulation results on two numerical examples are presented to substantiate the performance and characteristics of the multi-agent network.

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Section: Introductionmentioning

confidence: 99%

A Second-Order Multi-Agent Network for Bound-Constrained Distributed Optimization

Liu

Wang

2015

IEEE Trans. Automat. Contr.

321

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“…In [7], two distributed impulsive consensus protocols were proposed for linear multi-agent systems. Later, an improved impulsive consensus algorithm with less information transmission required was introduced in [5].…”

Section: Introductionmentioning

confidence: 99%

Network-based leader-following consensus of nonlinear multi-agent systems via distributed impulsive control

Chen

Han

et al. 2017

Information Sciences

288

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“…In the past decade, the cooperative control for multi-agent systems (MASs) has been intensively investigated in various disciplines for its fast development and wide applications in many fields (Ren, Beard, & Atkins(2005) ;Yang, Wang,& Li(2006) ;Jadbabaie, Lin, & Morse(2002); Ding,Yu,Liu,Guan, & Gang(2013)). The MASs are composed of a group of agents with limited computational capacity, where each agent can perceive states and transmit them each other.…”

Section: Introductionmentioning

confidence: 99%

Fast consensus algorithm of multi-agent systems with double gains regulation

Huang

Sun

Fan

et al. 2016

International Journal of Control

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Two novel fast consensus algorithms based on local information of first order discrete multi-agent systems under a directed network are proposed in this paper. By applying matrix theory and the frequencydomain analysis methods, two sufficient conditions about the convergence rate of the systems are presented respectively where the proportional-like gain feedback and incremental proportional-integral-differential (PID) gains feedback only with local information are added. Finally, a numerical example is given to show, the double gains regulation algorithm proposed in this paper has much faster consensus rate compared with the classical consensus algorithm in the same condition for its two-degree freedom parameters.

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Consensus of second-order multi-agent systems via impulsive control using sampled hetero-information

Cited by 48 publications

References 20 publications

A Second-Order Multi-Agent Network for Bound-Constrained Distributed Optimization

A Second-Order Multi-Agent Network for Bound-Constrained Distributed Optimization

Network-based leader-following consensus of nonlinear multi-agent systems via distributed impulsive control

Fast consensus algorithm of multi-agent systems with double gains regulation

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