Bounded consensus of double-integrator stochastic multi-agent systems

Abstract

<p style='text-indent:20px;'>In the framework of fixed topology and stochastic switching topologies, we study the mean-square bounded consensus(MSBC) of double-integrator stochastic multi-agent systems(SMASs) including additive system noises and communication noises. Combining algebra, graph theory and random analysis, we obtain several equivalent conditions for double-integrator SMASs to reach MSBC. In addition, the simulation examples also verify the correctness of the theoretical results.</p>

Necessary and sufficient conditions for mean‐square bounded consensus of multiagent systems with additive noise

“…. Since A 1 is not Hurwitz, we can get there is 𝜆(C 1 ) ≥ 0 such that lim t→∞ S(t) = ∞, which is contrary to (5).…”

“…The consensus problem of stochastic multiagent systems (MASs) has attracted attention because of its applications in traffic control [1], mobile robots [2], and social networks [3]. MASs considering noise interference in system and communication are studied in [4] and [5]. The authors in [6] use a distributed protocol to study MASs and the corresponding results are established.…”

Finite‐time adaptive consensus of stochastic multi‐agent systems with node‐based and edge‐based adaptive law design methods

“…With further refinement, Ming et al 37 allowed the topological switching of the system network to be driven by Markovian processes and the state of the system agents to be disturbed by stochastic noise. In addition, bounded consensus control of stochastic systems also attracts many scholars' interest, see References 38‐41. However, none of them used adaptive technologies.…”