Self-triggered Control with Energy Harvesting Sensor Nodes


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Date

2023-07

Publication Type

Journal Article

ETH Bibliography

yes

Citations

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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.

Publication status

published

Editor

Book title

Volume

7 (3)

Pages / Article No.

20

Publisher

Association for Computing Machinery

Event

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Distributed embedded systems; energy harvesting; self-triggered model predictive control; sensor networks; sustainable automatic control

Organisational unit

03429 - Thiele, Lothar (emeritus) / Thiele, Lothar (emeritus) check_circle

Notes

Funding

180545 - NCCR Automation (phase I) (SNF)

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