Data-driven Interval MDP for Robust Control Synthesis

• DOI: 10.48550/arxiv.2404.08344
• Publication Date: 2024-04-12
• Authors: Rudi Coppola; Andrea Peruffo; Licio Romao; Alessandro Abate; Manuel Mazo
• Keywords: Nondeterministic algorithm; Abstraction; Component (thermodynamics)

The abstraction of dynamical systems is a powerful tool that enables the design feedback controllers using correct-by-design framework. We investigate novel scheme to obtain data-driven abstractions discrete-time stochastic processes in terms richer discrete models, whose actions lead nondeterministic transitions over space probability measures. component proposed methodology lies fact we only assume samples from an unknown distribution. also rely on model underlying dynamics build our through backward reachability computations. nondeterminism captured by collection Markov Processes, and identify how this can improve upon existing techniques satisfying temporal properties, such as safety or reach-avoid. connection between made formal use scenario approach theory. Numerical experiments illustrate advantages main limitations with respect approaches.