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Resource Allocation with Stability Constraints of an Edge-cloud controlled AGV
arXiv - EE - Systems and Control Pub Date : 2023-01-23 , DOI: arxiv-2301.09388 Shreya Tayade, Peter Rost, Andreas Maeder, Hans Schotten
arXiv - EE - Systems and Control Pub Date : 2023-01-23 , DOI: arxiv-2301.09388 Shreya Tayade, Peter Rost, Andreas Maeder, Hans Schotten
The paper proposes Resource Allocation (RA) schemes for a closed loop
feedback control system by analysing the control-communication dependencies. We
consider an Automated Guided Vehicle (AGV) that communicates with a controller
located in an edge-cloud over a wireless fading channel. The control commands
are transmitted to an AGV and the position state is feedback to the controller
at every time-instant. A control stability based scheduling metric 'Probability
of Instability' is evaluated for the resource allocation. The performance of
stability based RA scheme is compared with the maximum SNR based RA scheme and
control error first approach in an overloaded and non-overloaded scenario. The
RA scheme with the stability constraints significantly reduces the resource
utilization and is able to schedule more number of AGVs while maintaining its
stability. Moreover, the proposed RA scheme is independent of control state and
depends upon consecutive packet errors, the control parameters like sampling
time and AGV velocity. Furthermore, we also analyse the impact of RA schemes on
the AGV's stability and error performance, and evaluated the number of unstable
AGVs.
中文翻译:
边缘云控制 AGV 稳定性约束下的资源分配
本文通过分析控制-通信依赖关系,提出了闭环反馈控制系统的资源分配 (RA) 方案。我们考虑一种自动导引车 (AGV),它通过无线衰落信道与位于边缘云中的控制器进行通信。控制命令被传输到AGV,并且位置状态在每个时刻被反馈到控制器。为资源分配评估基于控制稳定性的调度度量“不稳定概率”。在过载和非过载情况下,将基于稳定性的 RA 方案的性能与基于最大 SNR 的 RA 方案和控制误差优先方法进行了比较。具有稳定性约束的RA方案显着降低了资源利用率,并且能够在保持其稳定性的同时调度更多数量的AGV。此外,所提出的 RA 方案独立于控制状态,并取决于连续的数据包错误、采样时间和 AGV 速度等控制参数。此外,我们还分析了 RA 方案对 AGV 稳定性和错误性能的影响,并评估了不稳定 AGV 的数量。
更新日期:2023-01-26
中文翻译:
边缘云控制 AGV 稳定性约束下的资源分配
本文通过分析控制-通信依赖关系,提出了闭环反馈控制系统的资源分配 (RA) 方案。我们考虑一种自动导引车 (AGV),它通过无线衰落信道与位于边缘云中的控制器进行通信。控制命令被传输到AGV,并且位置状态在每个时刻被反馈到控制器。为资源分配评估基于控制稳定性的调度度量“不稳定概率”。在过载和非过载情况下,将基于稳定性的 RA 方案的性能与基于最大 SNR 的 RA 方案和控制误差优先方法进行了比较。具有稳定性约束的RA方案显着降低了资源利用率,并且能够在保持其稳定性的同时调度更多数量的AGV。此外,所提出的 RA 方案独立于控制状态,并取决于连续的数据包错误、采样时间和 AGV 速度等控制参数。此外,我们还分析了 RA 方案对 AGV 稳定性和错误性能的影响,并评估了不稳定 AGV 的数量。