Model-based dynamic periodic event-triggered control for nonlinear networked control systems with transmission delays
2024 (English)In: 2024 IEEE 63rd Conference on Decision and Control, CDC 2024, Institute of Electrical and Electronics Engineers (IEEE) , 2024, p. 1696-1701Conference paper, Published paper (Refereed)
Abstract [en]
This paper considers dynamic periodic eventtriggered control for nonlinear networked control systems. A model-based periodic event-triggering mechanism is proposed to potentially reduce the consumption of transmission resources for the networked control systems that are subject to time-varying inter-sampling intervals, transmission delays, and scheduling protocols. Furthermore, to compensate for the adverse effects of delays, the controller node is equipped with two specialized units: a propagation unit and a model unit. The role of propagation units is to work with the delayed data, using the data to estimate its current value and subsequently updating the state within the model unit. A predictor unit is employed at the sensor node to configure event-triggering conditions. A hybrid system framework is used to model the networked control systems. Moreover, sufficient conditions on the transmission intervals, delays and dynamic event-triggered control are given to ensure closed-loop asymptotic stability. Additionally, an allocation framework of the event-triggering mechanism is proposed, taking into account the information available at the sensor node. Finally, an example of a singlelink robot arm is simulated to illustrate the effectiveness and feasibility of the theoretical results.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2024. p. 1696-1701
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-361747DOI: 10.1109/CDC56724.2024.10886156Scopus ID: 2-s2.0-86000553426OAI: oai:DiVA.org:kth-361747DiVA, id: diva2:1948014
Conference
63rd IEEE Conference on Decision and Control, CDC 2024, Milan, Italy, Dec 16 2024 - Dec 19 2024
Note
Part of ISBN 9798350316339
QC 20250328
2025-03-272025-03-272025-03-28Bibliographically approved