AI & ML
Compute-Constrained Safety Filters with Neuromorphic Event Triggering
arXiv eess.SY0 views
arXiv:2610.10797v1 Announce Type: new Abstract: Safety filters that rely on control barrier function (CBF) quadratic programs (QPs) are typically analyzed under the assumption that the QP is solved instantaneously, although nonzero computation time can render a computed input unsafe by the time it is applied. This paper develops a dual leaky integrate-and-fire (LIF) event-triggered safety filter for linear systems that accounts for this delay. Two LIF states monitor a shifted CBF residual and the deviation of the held input from the nominal feedback law. A computation is initiated when either LIF state reaches its threshold; the previous input remains applied until the prescribed application time, and any solution returned earlier is stored until then. A closed-form charging profile relates the safety-LIF threshold to residual-growth bounds, ensuring sufficient residual margin over the application delay. Under the stated assumptions, the resulting hybrid system guarantees forward invariance, completeness, and non-Zeno execution, with positive lower bounds on computation-initiation and input-application times. A spacecraft terminal-approach simulation demonstrates safety with fewer optimizer calls than a delay-tightened periodic filter.
Source:https://arxiv.org/abs/2610.10797PreviousSafe Learning of Adaptive Control Policies for Remote Patient MonitoringNextHigh-Fidelity Baseline Design and Station Keeping Analyses for Earth-Moon Vertical Orbits
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