Asynchronous Event-Triggered Control for Non-Linear Systems
Daniel A. Williams, Airlie Chapman, Chris Manzie

TL;DR
This paper introduces a flexible asynchronous event-triggered control scheme for nonlinear systems that conserves network resources and avoids Zeno behavior, accommodating various sampling schemes.
Contribution
It extends existing ETC methods by allowing non-periodic, asynchronous sampling with hybrid dynamics and auxiliary timers to prevent Zeno behavior.
Findings
The scheme effectively manages asynchronous sampling in nonlinear control systems.
It prevents Zeno behavior using auxiliary timer variables.
Numerical example demonstrates practical applicability.
Abstract
With the increasing ubiquity of networked control systems, various strategies for sampling constituent subsystems' outputs have emerged. In contrast with periodic sampling, event-triggered control provides a way to efficiently sample a subsystem and conserve network resource usage, by triggering an update only when a state-dependent error threshold is satisfied. Herein we describe a novel scheme for asynchronous event-triggered measurement and control (ETC) of a nonlinear plant using sampler subsystems with hybrid dynamics. We extend existing ETC literature by adopting a more general representation of the sampler subsystem dynamics that do not require trigger periodicity or simultaneity, thus accommodating different sampling schemes for both synchronous and asynchronous ETC applications. We ensure that the plant and controller trigger rules are not susceptible to Zeno behavior by…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAtomic and Subatomic Physics Research · Advanced MRI Techniques and Applications · Quantum optics and atomic interactions
MethodsAttention Is All You Need · InfoNCE · Softmax · Position-Wise Feed-Forward Layer · Relative Position Encodings · Contrastive Predictive Coding · Linear Layer · Residual Connection · Multi-Head Attention · Dense Connections
