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H control for a class of multi-agent systems via a stochastic sampled-data method

机译:一类多智能体系统的随机抽样数据方法 H 控制

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In this study, the stochastic sampled-data approach is developed to deal with the control problem for a class of linear multi-agent systems. For each agent, signals should be transmitted to the control input, including not only its own measurements, but also the output information received from the neighbour agents. The relationships of information communications between the whole multi-agents are totally reflected by a weighted directed graph with a fixed topology structure. To the addressed problem, the author's focus is to design an output feedback controller for each agent such that, for the external energy bounded disturbances, the exponential stability in the mean square sense and interference rejection ability under consideration can be guaranteed. By assuming that the sampling period of each agent switches between two values in a probabilistic way, the stochastic sampling phenomenon is well characterised in every sampling tasks. In virtue of Lyapunov theory and semi-definite programming method, sufficient conditions are derived to ensure the exponential stability as well as performance, and the feedback controllers are also designed by solving some certain matrix inequalities. Finally, a numerical simulation is given to demonstrate the validness of the proposed control strategy.
机译:在这项研究中,开发了随机采样数据方法来处理一类线性多智能体系统的控制问题。对于每个代理,应该将信号传输到控制输入,不仅包括其自身的测量值,还包括从相邻代理接收的输出信息。整个多主体之间的信息通信关系完全由具有固定拓扑结构的加权有向图反映。针对此问题,作者的重点是为每个代理设计一个输出反馈控制器,这样,对于外部能量有界干扰,可以保证所考虑的均方根指数稳定性和抗干扰能力。通过假设每个代理的采样周期以概率的方式在两个值之间切换,随机采样现象在每个采样任务中都得到了很好的表征。借助李雅普诺夫理论和半定规划方法,推导了充分的条件来保证指数稳定性和性能,并通过求解某些矩阵不等式来设计反馈控制器。最后,通过数值仿真证明了所提控制策略的有效性。

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