Solving a modified consensus problem of linear multi-agent systems

Cheng, Long; Hou, Zeng-Guang; Lin, Yingzi; Tan, Min; Zhang, Wenjun

doi:10.1016/j.automatica.2011.03.014

Cited by 87 publications

(71 citation statements)

References 11 publications

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“…The consensus value is constant in [14], while it is dynamic in [15]. In our results, the consensus value is dynamic and explicitly given, and some variables of the state of each agent are convergent to a constant.…”

Section: Introductionmentioning

confidence: 75%

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r‐consensus control for discrete‐time high‐order multi‐agent systems

Xin

Cheng

2013

IET Control Theory & Applications

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This study considers a consensus problem of discrete-time high-order multi-agent systems with digraph. A concept r-consensus for discrete-time multi-agent systems is introduced, and consensus protocols are proposed for solving such problems. A sufficient and necessary condition for r-consensus is obtained using matrix theory. As a special case, criteria of r-consensus for third-order systems are given, in which the exact relationship of feedback parameters is established. Finally, the effectiveness of the theoretical results is demonstrated through a numerical simulation.

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Section: Introductionmentioning

confidence: 75%

“…It is noted that the consensus value is constant in most of the existing works such as [4,10,13,14], but dynamic in [9,11,15,16]. On the other hand, the consensus protocols are based on local relative information in [4,9,11,13,15,16], while based on local absolute and relative information in [10,14].…”

Section: Introductionmentioning

confidence: 99%

r‐consensus control for discrete‐time high‐order multi‐agent systems

Xin

Cheng

2013

IET Control Theory & Applications

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“…Next, the following assumptions are employed, where assumptions (A2) and (A4) are for a finite and nonzero consensus state and (A2) is inspired by [23]. Remark 3.…”

Section: Multiagent System Dynamics Consider a Class Of Mass Composimentioning

confidence: 99%

Distributed Consensus Design for a Class of Uncertain Linear Multiagent Systems under Unbalanced Randomly Switching Directed Topologies

Nguyễn

2018

Mathematical Problems in Engineering

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This paper proposes a novel approach to design fully distributed consensus controllers for heterogeneous linear Multiagent Systems subjected to randomly switching directed topologies and model uncertainties. The appealing features of this approach are as follows. First, it uses the mildest assumption for the randomly switching topologies that the union of switched graphs has a spanning tree. Second, the consensus is achieved under a class of state multiplicative uncertainties. Moreover, the proposed consensus controllers are low-rank and have nonconservative coupling strengths. Finally, a numerical example is presented to illustrate the effectiveness of the proposed theoretical approach.

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“…In such a case, we cannot designed the protocol based on the agent's full state. Motivated by [13,23,24], we designed the dynamic output-feedback protocol…”

Section: Protocol Designmentioning

confidence: 99%

Reaching a stochastic consensus in the noisy networks of linear MIMO agents: Dynamic output-feedback and convergence rate

Wang

Cheng

Yang

et al. 2015

Sci. China Technol. Sci.

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This paper addresses the leader-following consensus problem of linear multi-agent systems (MASs) with communication noise. Each agent's dynamical behavior is described by a linear multi-input and multi-output (MIMO) system, and the agent's full state is assumed to be unavailable. To deal with this challenge, a state observer is constructed to estimate the agent's full state. A dynamic output-feedback based protocol that is based on the estimated state is proposed. To mitigate the effect of communication noise, noise-attenuation gains are also introduced into the proposed protocol. In this study, each agent is allowed to have its own noise-attenuation gain. It is shown that the proposed protocol can solve the mean square leader-following consensus problem of a linear MIMO MAS. Moreover, if all noise-attenuation gains are of (t  ), where ∈(0,1), the convergence rate of the MAS can be quantitatively analyzed. It turns out that all followers' states converge to the leader's state in the mean square sense at a rate of O(t  ). multi-agent system, mean square consensus, communication noise, noise-attenuation gain, convergence rate Citation:Wang Y P, Cheng L, Yang C G, et al. Reaching a stochastic consensus in the noisy networks of linear MIMO agents: Dynamic output-feedback and convergence rate.

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Solving a modified consensus problem of linear multi-agent systems

Cited by 87 publications

References 11 publications

r‐consensus control for discrete‐time high‐order multi‐agent systems

r‐consensus control for discrete‐time high‐order multi‐agent systems

Distributed Consensus Design for a Class of Uncertain Linear Multiagent Systems under Unbalanced Randomly Switching Directed Topologies

Reaching a stochastic consensus in the noisy networks of linear MIMO agents: Dynamic output-feedback and convergence rate

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