  High performance but unverified controllers, e.g., artificial
intelligence-based (a.k.a. AI-based) controllers, are widely employed in
cyber-physical systems (CPSs) to accomplish complex control missions. However,
guaranteeing the safety and reliability of CPSs with this kind of controllers
is currently very challenging, which is of vital importance in many real-life
safety-critical applications. To cope with this difficulty, we propose in this
work a Safe-visor architecture for sandboxing unverified controllers in CPSs
operating in noisy environments (a.k.a. stochastic CPSs). The proposed
architecture contains a history-based supervisor, which checks inputs from the
unverified controller and makes a compromise between functionality and safety
of the system, and a safety advisor that provides fallback when the unverified
controller endangers the safety of the system. By employing this architecture,
we provide formal probabilistic guarantees on preserving the safety
specifications expressed by accepting languages of deterministic finite
automata (DFA). Meanwhile, the unverified controllers can still be employed in
the control loop even though they are not reliable. We demonstrate the
effectiveness of our proposed results by applying them to two (physical) case
studies.
