Model-bounded Monitoring of Hybrid Systems

Monitoring of hybrid systems attracts both scientific and practical attention. However, monitoring algorithms suffer from the methodological difficulty only observing sampled discrete-time signals, while real behaviors are continuous-time signals. To mitigate this problem sampling uncertainties, we introduce a model-bounded scheme, where use prior knowledge about target system to prune interpolation candidates. Technically, express such by linear automata (LHAs)—the LHAs called bounding models . We novel notion monitored language LHAs, reduce membership language. present two partial algorithms—one is via reduction reachability in other direct one using polyhedra—and show that these methods, thus proposed efficient practically relevant.