AI & ML
Robust Data-Driven Controller Synthesis from Sampled and Uncertain Frequency Response Estimates using Integral Quadratic Constraints
arXiv cs.SY0 views
arXiv:2610.20248v1 Announce Type: new Abstract: In this paper, we develop a novel MIMO controller synthesis method that relies solely on frequency-domain data of discrete-time systems. The approach is based on an iterative design procedure using \emph{integral quadratic constraints} (IQCs). It generalizes existing data-driven methods that approximate semi-infinite IQC conditions by enforcing them on a finite set of measured frequency points. Such approximations do not provide guarantees on the continuous frequency axis and may fail to capture inter-frequency behavior. We address this limitation by formulating a convex optimization problem that preserves robustness guarantees over the entire frequency range. In particular, the proposed method explicitly accounts for inter-frequency behavior of both plant and controller, leading to certified robust stability and performance. The effectiveness and computational efficiency of the approach are demonstrated using experimentally obtained frequency response data from industrial-grade semiconductor equipment. The synthesized controller is implemented on the physical setup, and its performance is validated in real-time experiments.
Source:https://arxiv.org/abs/2610.20248PreviousThe Cost of Executability: Temporal Margins for Continuous-Time Multi-Agent Path Finding under Closed-Loop ControlNextAsynchronous Distributed Multi-Sensor Fusion Over Sensor Track Hypotheses
Related posts
The Autonomous Edge — Issue #13: Cheaper Agents, Harder Governance (Week of November 2, 2026)
0dev.to AI

Plano Físico vs Plano Funcional en AWS Networking: cómo los arquitectos senior resuelven lo que otros no ven
0dev.to AWS
We built Origami Tutor: free paper-craft lessons you can turn and replay in 3D
0dev.to WebDev
From two authorized photos to a short AI rap video (consent-first workflow)
0dev.to WebDev
Check a File Hash in the Browser, Without Uploading the File
0dev.to WebDev
Your AI keys were leaked at a platform. A local guard you can paste catches the abuse before the invoice.
0dev.to Security