Safety-Critical Control with Input Delay in Dynamic Environment
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Abstract (arXiv)
Endowing nonlinear systems with safe behavior is increasingly important in modern control. This task is particularly challenging for real-life control systems that must operate safely in dynamically changing environments. This paper develops a framework for safety-critical control in dynamic environments, by establishing the notion of environmental control barrier functions (ECBFs). The framework is able to guarantee safety even in the presence of input delay, by accounting for the evolution of the environment during the delayed response of the system. The underlying control synthesis relies on predicting the future state of the system and the environment over the delay interval, with robust safety guarantees against prediction errors. The efficacy of the proposed method is demonstrated by a simple adaptive cruise control problem and a more complex robotics application on a Segway platform.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Dec 2021.
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Citing papers per year: 2024: 1; 2025: 2.
3 papers.
- 2025Stabilization of nonlinear systems with unknown delays via delay-adaptive neural operator approximate predictors30 Sep 2025
- 2025Delay-adaptive Control of Nonlinear Systems with Approximate Neural Operator Predictors28 Aug 2025
- 2024Domain Adaptive Safety Filters via Deep Operator Learning18 Oct 2024