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Data-Driven Stabilizing Controller Design for Linear Infi...
[Submitted on 16 Jun 2026] · 2026-06-17 · via cs updates on arXiv.org

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Abstract:We propose a direct data-driven method for controller synthesis of infinite networks composed of unknown linear time-invariant subsystems. Using a single set of noise-corrupted input-state trajectories collected from each subsystem, and provided that certain linear matrix inequalities hold, each subsystem is rendered exponentially input-to-state stable (eISS) by locally constructing an eISS control Lyapunov function together with an exponentially input-to-state stabilizing feedback controller. We then compose these local components under a compositional small-gain condition in infinite-dimensional spaces to obtain a global control Lyapunov function and an associated stabilizing controller, ensuring uniform global exponential stability of the infinite network. The approach is validated on a physical case study with unknown dynamics.

Submission history

From: Abolfazl Lavaei [view email]
[v1] Tue, 16 Jun 2026 04:40:31 UTC (1,352 KB)