Huan Luo

Mr. Huan Luo

orcid

Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 August 2021 in Entropy
Verified
Journal Article
Open access
PDF file
HLHuan Luo
Huan Luo
YWYinhe Wang
Yinhe Wang
RZRuidian Zhan
Ruidian Zhan
XZXuexi Zhang
Xuexi Zhang
HWHaoxiang Wen
Haoxiang Wen
SYSenquan Yang
Senquan Yang
This paper investigates the cluster-delay mean square consensus problem of a class of first-order nonlinear stochastic multi-agent systems with impulse time windows. Specifically, on the one hand, we have applied a discrete control mechanism (i.e., impulsive control) into the system instead of a continuous one, which has the advantages of low control cost, high convergence speed; on the other hand, we considered the existence of impulse time windows when modeling the system, that is, a single impulse appears randomly within a time window rather than an ideal fixed position. In addition, this paper also considers the influence of stochastic disturbances caused by fluctuations in the external environment. Then, based on algebraic graph theory and Lyapunov stability theory, some sufficiency conditions that the system must meet to reach the consensus state are given. Finally, we designed a simulation example to verify the feasibility of the obtained results.

26 April 2021 in Applied Sciences
Verified
Journal Article
Open access
PDF file
HLHuan Luo
Huan Luo
YWYinhe Wang
Yinhe Wang
XZXuexi Zhang
Xuexi Zhang
PGPeitao Gao
Peitao Gao
HWHaoxiang Wen
Haoxiang Wen
This paper focuses primarily on the mean square consensus problem of a class of nonlinear multi-agent systems suffering from stochastic impulsive deception attacks. The attacks here are modeled by completely stochastic destabilizing impulses, where their gains and instants satisfy all distributions and the Markovian process. Compared with existing methods, which assume that only gains are stochastic, it is difficult to deal with systems with different types of random variables. Thus, estimating the influence of these different types on the consensus problem is a key point of this paper. Based on the properties of stochastic processes, some sufficient conditions to solve the consensus problem are derived and some special cases are considered. Finally, a numerical example is given to illustrate the main results. Our results show that the consensus can be obtained if impulsive attacks do not occur too frequently, and it can promote system stability if the gains are below the defined threshold.