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From the 1 of 6 linked papers with an AI index.

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6 papers

math.OC2026

Robust Optimal Control of Arbitrarily Switched Systems: A Path-Complete Framework

Léa Ninite, Adrien Banse, Guillaume O. Berger +1

The paper proposes a framework for robust control of arbitrarily switched systems that simultaneously synthesizes a feedback policy and provides a certified upper bound on its infi…

math.OC2026

Iterative graph lifting for automatic design of path-complete stability certificates

Léa Ninite, Raphaël M. Jungers

Stability of switched linear systems under arbitrary switching is a fundamental problem in control theory, closely related to the joint spectral radius (JSR), which characterizes t…

math.OC2026

A Path-Complete Approach for Optimal Control of Switched Systems

Léa Ninite, Adrien Banse, Guillaume O. Berger +1

We study the problem of estimating the value function of discrete-time switched systems under arbitrary switching. Unlike the switched LQR problem, where both inputs and mode seque…

math.OC2025

Online Complexity Estimation for Repetitive Scenario Design

Guillaume O. Berger, Raphaël M. Jungers

We consider the problem of repetitive scenario design where one has to solve repeatedly a scenario design problem and can adjust the sample size (number of scenarios) to obtain a d…

math.OC2025

A Stochastic-Optimization-Based Adaptive-Sampling Scheme for Data-Driven Stability Analysis of Switched Linear Systems

Alexis Vuille, Guillaume O. Berger, Raphaël M. Jungers

We introduce a novel approach based on stochastic optimization to find the optimal sampling distribution for the data-driven stability analysis of switched linear systems. Our goal…

cs.LG2025

PAC Learnability of Scenario Decision-Making Algorithms: Necessary Conditions and Sufficient Conditions

Guillaume O. Berger, Raphaël M. Jungers

We investigate the Probably Approximately Correct (PAC) property of scenario decision algorithms, which refers to their ability to produce decisions with an arbitrarily low risk of…