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Game-based Abstraction and Controller Synthesis for Probabilistic Hybrid Systems

机译:概率混合系统的基于游戏的抽象和控制器综合

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We consider a class of hybrid systems that involve random phenomena, in addition to discrete and continuous behaviour. Examples of such systems include wireless sensing and control applications. We propose and compare two abstraction techniques for this class of models, which yield lower and upper bounds on the optimal probability of reaching a particular class of states. We also demonstrate the applicability of these abstraction techniques to the computation of long-run average reward properties and the synthesis of controllers. The first of the two abstractions yields more precise information, while the second is easier to construct. For the latter, we demonstrate how existing solvers for hybrid systems can be leveraged to perform the computation.
机译:除了离散和连续行为之外,我们考虑一类涉及随机现象的混合系统。这样的系统的示例包括无线感测和控制应用。我们提出并比较了此类模型的两种抽象技术,它们得出达到特定状态类别的最佳概率的上下界。我们还演示了这些抽象技术在长期平均奖励属性的计算和控制器合成中的适用性。两种抽象中的第一种产生更精确的信息,而第二种则更易于构造。对于后者,我们演示了如何利用现有的混合系统求解器来执行计算。

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