Delay Independent Safe Control with Neural Networks: Positive Lur'e Certificates for Risk Aware Autonomy

Hamidreza Montazeri Hedesh; Milad Siami

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arXiv · 2510.06661

Delay Independent Safe Control with Neural Networks: Positive Lur'e Certificates for Risk Aware Autonomy

Hamidreza Montazeri Hedesh·Milad Siami

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Abstract

We present a risk-aware safety certification method for autonomous, learning enabled control systems. Focusing on two realistic risks, state/input delays and interval matrix uncertainty, we model the neural network (NN) controller with local sector bounds and exploit positivity structure to derive linear, delay-independent certificates that guarantee local exponential stability across admissible uncertainties. To benchmark performance, we adopt and implement a state-of-the-art IQC NN verification pipeline. On representative cases, our positivity-based tests run orders of magnitude faster than SDP-based IQC while certifying regimes the latter cannot-providing scalable safety guarantees that complement risk-aware control.

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Hamidreza Montazeri Hedesh, Milad Siami. 2025-10-08. Delay Independent Safe Control with Neural Networks: Positive Lur'e Certificates for Risk Aware Autonomy. https://arxiv.org/abs/2510.06661

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