Quantitative Verification of Finite-Time Constrained Occupation Measures for Continuous-time Stochastic Systems
For control engineers designing autonomous systems with cumulative temporal requirements, this provides a new verification method for a previously unaddressed problem class.
This paper proposes a barrier-certificate framework to compute rigorous upper and lower bounds on the probability that a stochastic system satisfies finite-time constrained occupation specifications, validated via numerical examples.
This paper addresses the quantitative verification of finite-time constrained occupation time for stochastic continuous-time systems governed by stochastic differential equations (SDEs). Unlike classical reachability analysis, which focuses on single-event properties such as entering a target set, many autonomous tasks-including surveillance, wireless charging, and chemical mixing-require a system to accumulate a prescribed duration within a target region while strictly maintaining safety constraints. We propose a barrier-certificate framework to compute rigorous upper and lower bounds on the probability that such cumulative specifications are satisfied over a finite time horizon. By introducing a stopped process that freezes the system once it reaches the boundary of the safe set, we derive three classes of certificates: one for upper bounds and two for lower bounds. The proposed approaches are validated through numerical examples implemented using semidefinite programming.