arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2305.03399eess.SYcs.GTcs.SY
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基于上下文触发的抽象化控制设计

Context-triggered Abstraction-based Control Design

Satya Prakash Nayak, Lucas Neves Egidio, Matteo Della Rossa, Anne-Kathrin Schmuck, Raphaël Jungers

AI总结:

本文提出两层抽象化控制综合方法,利用下层不变集、吸引域与上层有限博弈求解,为非线性系统自动设计满足上下文相关 LTL 规范且可扩展的混合控制器。

摘要:

我们研究为非线性动力系统自动综合混合控制器的问题,该控制器需确保闭环系统满足任意 Linear Temporal Logic(线性时序逻辑)规范。此外,该规范还可考虑由外部环境或系统自身引发的逻辑上下文切换。最后,为保证可扩展性,我们希望避免传统的暴力时间与空间离散化方法。为此,我们提出一种新颖的两层策略综合方法:下层生成的控制器提供不变集和吸引域,上层逻辑层则以抽象方式利用这些集合。为实现这一目标,我们为上层和下层综合均提供了新技术。我们的新方法能够以可扩展的方式,同时利用状态空间控制技术的计算能力与有限博弈求解在处理复杂规范方面的智能。

英文摘要:

We consider the problem of automatically synthesizing a hybrid controller for non-linear dynamical systems which ensures that the closed-loop fulfills an arbitrary \emph{Linear Temporal Logic} specification. Moreover, the specification may take into account logical context switches induced by an external environment or the system itself. Finally, we want to avoid classical brute-force time- and space-discretization for scalability. We achieve these goals by a novel two-layer strategy synthesis approach, where the controller generated in the lower layer provides invariant sets and basins of attraction, which are exploited at the upper logical layer in an abstract way. In order to achieve this, we provide new techniques for both the upper- and lower-level synthesis. Our new methodology allows to leverage both the computing power of state space control techniques and the intelligence of finite game solving for complex specifications, in a scalable way.

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。

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