Dionysos.jl: a Modular Platform for Smart Symbolic Control

Abstract

We introduce Dionysos.jl, a modular package for solving optimal control problems for complex dynamical systems using state-of-the-art and experimental techniques from symbolic control, optimization, and learning. More often than not with Cyber-Physical systems, the only sensible way of developing a controller is by discretizing the different variables, thus transforming the control task into a purely combinatorial problem on a finite-state mathematical object, called an abstraction of this system. Although this approach offers a safety-critical framework, the available techniques suffer important scalability issues. In order to render these techniques practical, it is necessary to construct smarter abstractions that differ from classical techniques by partitioning the state-space in a non trivial way.

arXiv commentPublished in the JuliaCon Proceedings

References in corpus (5)

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• IntervalMDP.jl: Accelerated Value Iteration for Interval Markov Decision Processes
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