Self-triggered Control with Energy Harvesting Sensor Nodes

IF 2 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS ACM Transactions on Cyber-Physical Systems Pub Date : 2023-05-17 DOI:10.1145/3597311
Naomi Stricker, Yingzhao Lian, Yuning Jiang, Colin N. Jones, L. Thiele
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Abstract

Distributed embedded systems are pervasive components jointly operating in a wide range of applications. Moving toward energy harvesting powered systems enables their long-term, sustainable, scalable, and maintenance-free operation. When these systems are used as components of an automatic control system to sense a control plant, energy availability limits when and how often sensed data are obtainable and therefore when and how often control updates can be performed. The time-varying and non-deterministic availability of harvested energy and the necessity to plan the energy usage of the energy harvesting sensor nodes ahead of time, on the one hand, have to be balanced with the dynamically changing and complex demand for control updates from the automatic control plant and thus energy usage, on the other hand. We propose a hierarchical approach with which the resources of the energy harvesting sensor nodes are managed on a long time horizon and on a faster timescale, self-triggered model predictive control controls the plant. The controller of the harvesting-based nodes’ resources schedules the future energy usage ahead of time and the self-triggered model predictive control incorporates these time-varying energy constraints. For this novel combination of energy harvesting and automatic control systems, we derive provable properties in terms of correctness, feasibility, and performance. We evaluate the approach on a double integrator and demonstrate its usability and performance in a room temperature and air quality control case study.
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能量收集传感器节点的自触发控制
分布式嵌入式系统是在广泛的应用中共同运行的普遍组件。朝着能量收集供电系统的方向发展,可以实现其长期、可持续、可扩展和免维护的运行。当这些系统用作自动控制系统的组件来感知控制工厂时,能源可用性限制了何时和多久可以获得感测数据,从而限制了何时和多久可以执行控制更新。一方面,收集能量的时变和不确定性可用性,以及提前规划能量收集传感器节点的能量使用的必要性,必须与自动控制装置对控制更新的动态变化和复杂需求以及能源使用进行平衡,另一方面。我们提出了一种分层方法,该方法可以在较长的时间范围内管理能量收集传感器节点的资源,并且在更快的时间尺度上,自触发模型预测控制可以控制工厂。基于收获的节点资源控制器提前调度未来的能源使用,自触发模型预测控制将这些时变的能源约束纳入其中。对于这种能量收集和自动控制系统的新组合,我们在正确性、可行性和性能方面得出了可证明的性质。我们在双积分器上评估了该方法,并在室温和空气质量控制案例研究中展示了其可用性和性能。
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来源期刊
ACM Transactions on Cyber-Physical Systems
ACM Transactions on Cyber-Physical Systems COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
5.70
自引率
4.30%
发文量
40
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