Mean-square consensus of heterogeneous multi-agent systems with communication noises

Guo, Shaoyan; Mo, Lipo; Yu, Yongguang

doi:10.1016/j.jfranklin.2018.03.002

Cited by 41 publications

(32 citation statements)

References 22 publications

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“…When w 2 = 0 and have no formation requirements for the agents, the problem considered herein degenerate into the mean-square consensus problem which was investigated [8]. Generally speaking, the problem considered in Lin and Jia [7], Guo et al [17], and Mo et al [20] all can be seen as a special case of this paper.…”

Section: Remarkmentioning

confidence: 98%

“…Then, the origin system can be decoupled into the following system: [15], Cheng et al [16], Guo et al [17], Sun et al [18], and Mo et al [19], where the mean square consensus control of MASs was investigated, the mean-square quasicomposite rotating formation control of MASs is investigated in this paper. Since the formation is considered and a time-varying consensus gain is introduced into the control protocol to attenuate the stochastic communication noises, though the origin closed-loop system is changed into an equivalent closed-loop system by taking a coordinate transformation, it is still difficult to obtain the eigenvector of the matrix.…”

Section: T J C T J a T A C T C T J A Tmentioning

confidence: 99%

“…Since the formation is considered and a time-varying consensus gain is introduced into the control protocol to attenuate the stochastic communication noises, though the origin closed-loop system is changed into an equivalent closed-loop system by taking a coordinate transformation, it is still difficult to obtain the eigenvector of the matrix. Therefore, the methods proposed in Li and Zhang [15], Cheng et al [16], Guo et al [17], Sun et al [18], and Mo et al [19] cannot be directly extended to solve the problem proposed herein.…”

Section: T J C T J a T A C T C T J A Tmentioning

confidence: 99%

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Mean-square Quasi-composite Rotating Formation Control of Second-order Multi-agent Systems under Stochastic Communication Noises

Yuan

Jia

et al. 2019

JRNAL

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Recently, to imitate or explain such kinds of motions, the collective rotating motions of second-order MASs was investigated in Lin and Jia [7], based on which, Lin et al. [8], made a further study on the distributed composite-rotating consensus of second-order MASs. Furthermore, rotating consensus [9], common finite-time rotating encirclement control [10], and the influence of non-uniform delays on distributed rotating consensus [11] was investigated. Moreover, notice the fact that, groups of agents may require to maintain desired formation during this process, therefore, the formation control of MASs was investigated, such as Xiao et al. [12], Xue et al. [13], and Meng et al. [14]. Notice that the above-mentioned works all assumed that the information exchange between different agents is ideal, that is, each agent can obtain its neighbor's information accurately. However, in reality, the communications among different agents may be interfered by stochastic communication noise, which may lead to great negative influence on the stability of the system. It is meaningful to design proper control protocol such that the stochastic communication noises can be countered. The consensus control problem of MASs with communication noises were solved in Li and Zhang [15], Cheng et al. [16], Guo et al. [17], and Sun et al. [18]. The mean-square composite-rotating consensus problem of second-order MASs with communication noises was addressed by introducing a time-varying consensus gain in the control protocol [19]. Since the formation is considered and a time-varying consensus gain is introduced into the control protocol to attenuate the stochastic communication noises, though the origin closedloop system is changed into an equivalent closed-loop system by taking a coordinate transformation, it is still difficult to obtain the eigenvector of the matrix. Therefore, the methods proposed in Li and Zhang [15], Cheng et al. [16], Guo et al. [17], Sun et al. [18], and Mo et al. [19] cannot be directly extended to achieve the quasicomposite rotating formation control of MASs under stochastic communication noises. Up-to-date, it is a pity to find that there is no result on composite-rotating formation control of MASs with stochastic communication noises. Motivated by the above discussions, the mean-square quasicomposite rotating formation control of second-order MASs with stochastic communication noises is considered in this paper

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Section: Remarkmentioning

confidence: 98%

Section: T J C T J a T A C T C T J A Tmentioning

confidence: 99%

Section: T J C T J a T A C T C T J A Tmentioning

confidence: 99%

See 1 more Smart Citation

Mean-square Quasi-composite Rotating Formation Control of Second-order Multi-agent Systems under Stochastic Communication Noises

Yuan

Jia

et al. 2019

JRNAL

Self Cite

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“…In addition, if the graph  is still a connected graph, then its second smallest eigenvalue must satisfy Lemma 2. [27] The necessary and sufficient condition for the topologȳ  to be connected is that all eigenvalues of M are greater then 0.…”

Section: Problem Formulationsmentioning

confidence: 99%

Mean‐square output consensus of heterogeneous multi‐agent systems with communication noises

Chen

Ren

et al. 2021

IET Control Theory & Appl

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This paper focuses on the mean‐square output consensus of heterogeneous multi‐agent systems, in which the communication noises are taken into consideration. Through internal model principle and control gain function, the novel state feedback and output feedback control strategies are designed for leaderless and a leader situation respectively to attenuate disturbances caused by communication noises. In addition, based on matrix theory and stochastic analysis, the sufficient condition for output consensus in the corresponding case is obtained. In the end, the simulations are used to confirm the correctness of the conclusion.

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“…However, in reality, due to the complexity of environment, it is usually required various agents cooperate with each other to complete a task that cannot be done by a single agent. When different types of agents work together, due to the influence of external environment, communication conditions and their different attributes, agents in a system usually have different dynamics 13,16‐21 . Therefore, it is important to study the heterogeneous multi‐agent systems (HMAS) 20,22‐26 .…”

Section: Introductionmentioning

confidence: 99%

Consensus of heterogeneous discrete‐time multi‐agent systems with noise over Markov switching topologies

Sun

Lei

Kurths

2020

Intl J Robust & Nonlinear

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This paper considers the mean‐square bounded consensus of heterogeneous discrete‐time multi‐agent systems with noise over fixed and Markov switching topologies. Firstly, a protocol is designed based on the agents' neighbor information with noise. Secondly, by using the Lyapunov function method, matrix analysis and probability theory, sufficient conditions for the mean‐square bounded consensus are given. Finally, several simulations are presented to illustrate the potential correctness of the results.

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Mean-square consensus of heterogeneous multi-agent systems with communication noises

Cited by 41 publications

References 22 publications

Mean-square Quasi-composite Rotating Formation Control of Second-order Multi-agent Systems under Stochastic Communication Noises

Mean-square Quasi-composite Rotating Formation Control of Second-order Multi-agent Systems under Stochastic Communication Noises

Mean‐square output consensus of heterogeneous multi‐agent systems with communication noises

Consensus of heterogeneous discrete‐time multi‐agent systems with noise over Markov switching topologies

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