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Finite-horizon H-infinity-consensus control for multi-agent systems with random parameters: The local condition case

机译:具有随机参数的多智能体系统的有限水平H-无穷大共识控制:局部情况

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摘要

This paper is concerned with the distributed H-infinity-consensus control problem over the finite horizon for a class of discrete time-varying multi-agent systems with random parameters. First, by utilizing the proposed information matrix, a new formula is established to calculate the weighted covariance matrix of random matrix. Next, by allowing every agent to track the average of the neighbor agents, a novel local H-infinity-consensus performance constraint is presented to cater to the local performance analysis. Then, by means of the proposed definition of the stochastic vector dissipativity-like over the finite horizon, a set of sufficient conditions for every agent is obtained such that the controlled outputs of the closed-loop multi-agent systems satisfy the proposed H-infinity-consensus performance constraint. As a result, the proposed consensus control algorithm can be executed on each agent in an indeed distributed manner. Finally, a simulation example is employed to verify the effectiveness of the proposed algorithm. (C) 2017 Published by Elsevier Ltd on behalf of The Franklin Institute.
机译:本文涉及一类具有随机参数的离散时变多智能体系统在有限水平上的分布式H-无穷共识控制问题。首先,利用提出的信息矩阵,建立一个新的公式来计算随机矩阵的加权协方差矩阵。接下来,通过允许每个代理跟踪相邻代理的平均值,提出了一种新颖的局部H-无穷大共识性能约束,以迎合本地性能分析。然后,通过对有限水平上的随机矢量耗散性的拟议定义,获得了每个代理的一组充分条件,使得闭环多代理系统的受控输出满足拟议的H-无穷大。 -共识性能约束。结果,可以以确实分布式的方式在每个代理上执行所提出的共识控制算法。最后,通过仿真实例验证了所提算法的有效性。 (C)2017由Elsevier Ltd代表富兰克林研究所出版。

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  • 来源
    《Journal of the Franklin Institute》 |2017年第14期|6078-6097|共20页
  • 作者单位

    Univ Shanghai Sci & Technol, Business Sch, Shanghai 200093, Peoples R China|Northeast Petr Univ, Inst Complex Syst & Adv Control, Daqing 163318, Peoples R China|Northeast Petr Univ, Heilongjiang Prov Key Lab Networking & Intelligen, Daqing 163318, Peoples R China;

    Univ Shanghai Sci & Technol, Dept Control Sci & Engn, Shanghai Key Lab Modern Opt Syst, Shanghai 200093, Peoples R China;

    Swinburne Univ Technol, Sch Software & Elect Engn, Melbourne, Vic 3122, Australia;

    Univ Shanghai Sci & Technol, Dept Control Sci & Engn, Shanghai Key Lab Modern Opt Syst, Shanghai 200093, Peoples R China;

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  • 入库时间 2022-08-18 02:57:43

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