arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 2102.12734eess.SYcs.SY
收藏

基于时间序列数据的仿射动力学混合自动机综合

Synthesis of Hybrid Automata with Affine Dynamics from Time-Series Data

Miriam García Soto, Thomas A. Henzinger, Christian Schilling

摘要:

嵌入式和信息物理系统的形式化设计依赖于数学建模。本文考虑一类动力学由仿射微分方程定义的混合自动机模型。给定一组时间序列数据,我们提出了一种算法方法来合成一个混合自动机表现出的行为是接近的数据,达到指定的精度,并与数据同步的变化。在我们的合成算法的一个基本问题是检查的时间序列的混合自动机的成员。我们的解决方案集成了仿射动力系统的可达性和优化技术,以获得成员资格的充分和必要条件,结合在一个细化框架。该算法一次处理一个时间序列,因此可以中断,提供中间结果,并恢复。我们报告的实验结果表明,我们的合成方法的适用性。

英文摘要:

Formal design of embedded and cyber-physical systems relies on mathematical modeling. In this paper, we consider the model class of hybrid automata whose dynamics are defined by affine differential equations. Given a set of time-series data, we present an algorithmic approach to synthesize a hybrid automaton exhibiting behavior that is close to the data, up to a specified precision, and changes in synchrony with the data. A fundamental problem in our synthesis algorithm is to check membership of a time series in a hybrid automaton. Our solution integrates reachability and optimization techniques for affine dynamical systems to obtain both a sufficient and a necessary condition for membership, combined in a refinement framework. The algorithm processes one time series at a time and hence can be interrupted, provide an intermediate result, and be resumed. We report experimental results demonstrating the applicability of our synthesis approach.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑