Data-Driven Safety Verification of Discrete-Time Networks: A Compositional Approach

This letter proposes a compositional data-driven approach for safety verification of networks discrete-time subsystems with formal guarantees . Following modular and each subsystem, we search so-called sub-barrier candidate represented as linear combination priori user-defined basis functions. We formulate the conditions on candidates robust convex programs (RCPs) which are semi-infinite programs. Collecting sampled data from approximate RCP via scenario program (SCP) is finite program. provide an xmlns:xlink="http://www.w3.org/1999/xlink">explicit formula to compute minimum number guaranteeing desired mismatch between optimal value that corresponding SCP in probabilistic sense. To ensure sum barrier function whole network, define global dissipativity condition top local SCPs. The SCPs thus related other this condition. results large-scale optimization problem standard canonical form efficiently solved by alternating direction method multipliers (ADMM) algorithm. effectiveness our illustrated applying it room temperature control 100-room building.