Risk‐Aware Control: Integrating Worst‐Case Conditional Value‐At‐Risk With Control Barrier Function

ABSTRACT In safety‐critical control systems such as autonomous vehicles and medical devices, managing the risk of rare but severe tail events under uncertainty is crucial. This paper addresses this challenge by proposing a risk‐aware control framework that integrates the worst‐case conditional value‐at‐risk (CVaR) with control barrier functions (CBFs). Specifically, we formulate risk‐aware safety constraints based on the worst‐case CVaR, and show that the resulting risk‐aware controllers can be computed via quadratic programs (for half‐space and polytopic safe sets) or a semidefinite program (for ellipsoidal safe sets). Numerical simulations on an inverted pendulum illustrate that the proposed approach ensures safety under various scenarios and significantly reduces the safety constraint violation compared to existing CBF approaches. Overall, we show that incorporating worst‐case CVaR into CBF design offers a tractable solution for safety‐critical applications under uncertainty.

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Publication Details

Journal
IET Control Theory and Applications
Published
2025-01-01
DOI
https://doi.org/10.1049/cth2.70024
Citations
1
Primary Topic
Risk and Portfolio Optimization
Type
article
Field-Weighted Citation Impact
2.11

Funders

Controls
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article

Risk‐Aware Control: Integrating Worst‐Case Conditional Value‐At‐Risk With Control Barrier Function

Masako Kishida
1 citations
IET Control Theory and Applications
Risk and Portfolio Optimization
2.11
article

Risk‐Aware Control: Integrating Worst‐Case Conditional Value‐At‐Risk With Control Barrier Function

Masako Kishida
article en
1 citations

Abstract

ABSTRACT In safety‐critical control systems such as autonomous vehicles and medical devices, managing the risk of rare but severe tail events under uncertainty is crucial. This paper addresses this challenge by proposing a risk‐aware control framework that integrates the worst‐case conditional value‐at‐risk (CVaR) with control barrier functions (CBFs). Specifically, we formulate risk‐aware safety constraints based on the worst‐case CVaR, and show that the resulting risk‐aware controllers can be computed via quadratic programs (for half‐space and polytopic safe sets) or a semidefinite program (for ellipsoidal safe sets). Numerical simulations on an inverted pendulum illustrate that the proposed approach ensures safety under various scenarios and significantly reduces the safety constraint violation compared to existing CBF approaches. Overall, we show that incorporating worst‐case CVaR into CBF design offers a tractable solution for safety‐critical applications under uncertainty.

IET Control Theory and ApplicationsVol. 19(1)
National Institute of Informatics (JP)
Precursory Research for Embryonic Science and Technology
Openalex Percentile: Top 15%
Risk and Portfolio Optimization
2.11
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