We present a data-driven framework based on Lyapunov theory to provide stability guarantees for a family of hybrid systems. In particular, we are interested in the asymptotic stability of switching linear systems whose switching sequence is constrained by labeled graphs, namely constrained switching linear systems. In order to do so, we provide chance-constrained bounds on stability guarantees, that can be obtained from a finite number of observations with bounded noise. We first present a method providing stability guarantees from sampled trajectories in the hybrid state space of the system. We then study the harder situation where one only observes the continuous part of the hybrid states. We show that in this case, one may still obtain formal chance-constrained stability guarantees. For this latter result we provide a new upper bound of general interest, also for model-based stability analysis.

我们提出了一个基于李亚普诺夫理论的数据驱动框架，为一系列混合系统提供稳定性保证。我们特别感兴趣的是其切换序列受标记图约束的切换线性系统的渐近稳定性，即约束切换线性系统。为了做到这一点，我们提供了稳定性保证的机会约束界限，这可以从有限数量的具有有限噪声的观察中获得。我们首先提出一种从系统混合状态空间中的采样轨迹提供稳定性保证的方法。然后我们研究更困难的情况，即人们只观察到连续部分混合状态。我们表明，在这种情况下，人们仍然可以获得正式的机会约束稳定性保证。对于后一个结果，我们提供了一个新的普遍关注的上限，也适用于基于模型的稳定性分析。