BOCoSy: Small but Powerful Symbolic Output-Feedback Control

Bernd Finkbeiner, Kaushik Mallik, Noemi Passing, Malte Schledjewski, Anne-Kathrin Schmuck

We present BOCoSy, a tool for bounded symbolic output-feedback controller synthesis. BOCoSy synthesizes symbolic output-feedback controllers which interact with a given plant via a pre-defined finite symbolic interface. BOCoSy solves this problem by a new lazy abstraction-refinement technique which starts with a very coarse abstraction of the external trace semantics of the given plant and iteratively removes non-admissible behavior from this abstract model until a controller is found. BOCoSy steers the search for controllers towards small and concise state space representations by utilizing ideas from bounded synthesis. As a result, BOCoSy returns small and explainable controllers that are still powerful enough to solve the given synthesis problem. We show that BOCoSy is able to synthesize small, human readable symbolic controllers quickly on a set of benchmarks.

25th ACM International Conference on Hybrid Systems - Computation and Control (HSCC 2022).

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