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Electrical Engineering and Systems Science > Systems and Control

arXiv:2509.01777 (eess)
[Submitted on 1 Sep 2025 (v1) , last revised 8 Sep 2025 (this version, v2)]

Title: Maximally Resilient Controllers under Temporal Logic Specifications

Title: 在时间逻辑规范下的最大弹性控制器

Authors:Youssef Ait Si, Ratnangshu Das, Negar Monir, Sadegh Soudjani, Pushpak Jagtap, Adnane Saoud
Abstract: In this paper, we consider the notion of resilience of a dynamical system, defined by the maximum disturbance a controlled dynamical system can withstand while satisfying given temporal logic specifications. Given a dynamical system and a specification, the objective is to synthesize the controller such that the closed-loop system satisfies this specification while maximizing its resilience. The problem is formulated as a robust optimization program where the objective is to compute the maximum resilience while simultaneously synthesizing the corresponding controller parameters. For linear systems and linear controllers, exact solutions are provided for the class of time-varying polytopic specifications. For the case of nonlinear systems, nonlinear controllers and more general specifications, we leverage tools from the scenario optimization approach, offering a probabilistic guarantee of the solution as well as computational feasibility. Different case studies are presented to illustrate the theoretical results.
Abstract: 在本文中,我们考虑动态系统的弹性概念,该概念由受控动态系统在满足给定时序逻辑规范的同时所能承受的最大扰动来定义。 给定一个动态系统和一个规范,目标是合成控制器,使得闭环系统满足该规范,同时最大化其弹性。 该问题被表述为一个鲁棒优化程序,其中目标是在同时合成相应控制器参数的同时计算最大弹性。 对于线性系统和线性控制器,提供了时变多面体规范类的精确解。 对于非线性系统、非线性控制器和更一般的规范情况,我们利用了场景优化方法中的工具,提供了该解的概率保证以及计算可行性。 不同的案例研究被提出以说明理论结果。
Comments: 8 pages, 4 figures, conference
Subjects: Systems and Control (eess.SY) ; Optimization and Control (math.OC)
Cite as: arXiv:2509.01777 [eess.SY]
  (or arXiv:2509.01777v2 [eess.SY] for this version)
  https://doi.org/10.48550/arXiv.2509.01777
arXiv-issued DOI via DataCite

Submission history

From: Youssef Ait Si [view email]
[v1] Mon, 1 Sep 2025 21:22:49 UTC (1,052 KB)
[v2] Mon, 8 Sep 2025 18:55:54 UTC (1,052 KB)
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