Constrained Optimization for Hybrid System Falsification and Application to Conjunctive Synthesis

Abstract The synthesis problem of a cyber-physical system (CPS) is to find an input signal under which the system’s behavior satisfies a given specification. Our setting is that the specification is a formula of signal temporal logic, and furthermore, that the specification is a conjunction of different and often conflicting requirements. Conjunctive synthesis is often challenging for optimization-based falsification—an established method for CPS analysis that can also be used for synthesis—since the usual framework (especially how its robust semantics handles Boolean connectives) is not suited for finding delicate trade-offs between different requirements. Our proposed method consists of a combination of optimization-based falsification and constrained optimization. Specifically, we show that the state-of-the-art multiple constraint ranking method can be combined with falsification powered by CMA-ES optimization; its performance advantage for conjunctive synthesis is demonstrated in experiments.