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IP Traffic Modelling in Scalable Drone Network for Carrying Scalable Logistic Operations

机译:可伸缩无人机网络中的IP流量建模,用于携带可扩展物流操作

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摘要

This study presents a self modelling method for control system of multi-coupled non-linear scalable drones based logistic services with the help of second-order dynamics of communicating membrane system by realizing consensus. This usually requires a layered multiple network control architecture designed mainly for coordinating access of various unmanned aerial vehicles to control airspace, package delivery, rescue, traffic surveillance and more. Here, the communicating membrane system is modelled based on the theory of fractional differential equations. At every interval of the sampling time, all the subsystems are optimally synchronized in P population system by multiset-rewriting rules including the effect of symport/antiport systems. Model of the minimal symport or antiport is also derived to ensure the universality for P systems with multiset-rewriting rules. Further research in this domain will enable the development of evolving architecture of a non-linear cyber physical system. The close loop stability and the recursive feasibility of the evolved architecture are also studied. Comparison are also drawn predictive control to prove the effectiveness of the proposed system.
机译:本研究通过实现共识,介绍了基于多耦合非线性可伸缩无人机的控制系统的自模建筑方法,该方法通过实现膜系统的二阶动态。这通常需要分层多网络控制架构,该架构主要设计用于协调各种无人机车辆的访问,以控制空域,包装递送,救援,交通监测等。这里,基于分数微分方程理论建模的通信膜系统。在采样时间的每个间隔,所有子系统都是通过包括Symport / Antiport系统的效果的多立方重写规则在P人口系统中最佳地同步。还导出了最小次端口交或反序列的模型,以确保具有多重重写规则的P系统的普遍性。该域的进一步研究将能够开发非线性网络物理系统的不断变化的架构。还研究了近循环稳定性和进化架构的递归可行性。比较也是绘制预测控制,以证明所提出的系统的有效性。

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