When Sampling Works in Data-Driven Control: Informativity for Stabilization in Continuous Time

• 成果类型: Article
• 署名作者: Eising, Jaap; Cortes, Jorge
• 署名单位: Swiss Federal Institutes of Technology Domain; ETH Zurich; University of California System; University of California San Diego
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2024.3438348
• 发表日期: 2025
• 关键词: systems

摘要

This article introduces a notion of data informativity for stabilization tailored to continuous-time signals and systems. We establish results comparable to those known for discrete-time systems with sampled data. We justify that additional assumptions on the properties of the noise signals are needed to understand when sampled versions of continuous-time signals are informative for stabilization, thereby introducing the notions of square Lipschitzness and total bounded variation. This allows us to connect the continuous and discrete domains, yielding sufficient conditions to synthesize a stabilizing controller for the true continuous-time system on the basis of sampled data. Simulations illustrate our results.