Exponential-Condition-Based Barrier Certificate Generation for Safety Verification of Hybrid Systems
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Abstract (arXiv)
A barrier certificate is an inductive invariant function which can be used for the safety verification of a hybrid system. Safety verification based on barrier certificate has the benefit of avoiding explicit computation of the exact reachable set which is usually intractable for nonlinear hybrid systems. In this paper, we propose a new barrier certificate condition, called Exponential Condition, for the safety verification of semi-algebraic hybrid systems. The most important benefit of Exponential Condition is that it has a lower conservativeness than the existing convex condition and meanwhile it possesses the property of convexity. On the one hand, a less conservative barrier certificate forms a tighter over-approximation for the reachable set and hence is able to verify critical safety properties. On the other hand, the property of convexity guarantees its solvability by semidefinite programming method. Some examples are presented to illustrate the effectiveness and practicality of our method.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Mar 2013.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 1.
3 papers.
- 2022Joint Differentiable Optimization and Verification for Certified Reinforcement Learningcited by 11
- 2024Verification-Aided Learning of Neural Network Barrier Functions with Termination Guaranteescited by 7
- 2025BarrierBench: Evaluating Large Language Models for Safety Verification in Dynamical Systemscited by 0
- 2025BarrierBench: Evaluating Large Language Models for Safety Verification in Dynamical Systems12 Nov 2025
- 2024Verification-Aided Learning of Neural Network Barrier Functions with Termination Guarantees12 Mar 2024
- 2022Joint Differentiable Optimization and Verification for Certified Reinforcement Learning28 Jan 2022