Encoding inductive invariants as barrier certificates: Synthesis via difference-of-convex programming

Information and Computation(2022)

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We present the invariant barrier-certificate condition that witnesses unbounded-time safety of differential dynamical systems. The proposed condition is the weakest possible one to attain inductive invariance. We show that discharging the invariant barrier-certificate condition —thereby synthesizing invariant barrier certificates— can be encoded as solving an optimization problem subject to bilinear matrix inequalities (BMIs). We further propose a synthesis algorithm based on difference-of-convex programming, which approaches a local optimum of the BMI problem via solving a series of convex optimization problems. This algorithm is incorporated in a branch-and-bound framework that searches for the global optimum in a divide-and-conquer fashion. We present a weak completeness result of our method, namely, a barrier certificate is guaranteed to be found (under some mild assumptions) whenever there exists an inductive invariant (in the form of a given template) that suffices to certify safety. Experimental results on benchmarks demonstrate the effectiveness and efficiency of our approach.
Barrier certificates,Inductive invariants,Bilinear matrix inequalities,Difference-of-convex programming,Semidefinite programming
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