Controller Synthesis from Noisy-Input Noisy-Output Data
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Abstract (arXiv)
We consider the problem of synthesizing a dynamic output-feedback controller for a linear system, using solely input-output data corrupted by measurement noise. To handle input-output data, an auxiliary representation of the original system is introduced. By exploiting the structure of the auxiliary system, we design a controller that robustly stabilizes all possible systems consistent with data. Notably, we also provide a novel solution to extend the results to generic multi-input multi-output systems. The findings are illustrated by numerical examples.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 14 of its 30 references that are in the map. First posted on arXiv 4 Feb 2024.
Builds on
14 of 30 references.
References · 14
- 2019Formulas for Data-driven Control: Stabilization, Optimality and Robustnesscited by 40
- 2018Data-Enabled Predictive Control: In the Shallows of the DeePCcited by 33
- 2020Combining Prior Knowledge and Data for Robust Controller Designcited by 9
- 2020Provably robust verification of dissipativity properties from datacited by 3
- 2021Data-driven control via Petersen's lemmacited by 2
- 2021On a Stochastic Fundamental Lemma and Its Use for Data-Driven Optimal Controlcited by 2
- 2022Quadratic matrix inequalities with applications to data-based controlcited by 2
- 2022A behavioral approach to data-driven control with noisy input-output datacited by 2
- 2021On data-driven control: informativity of noisy input-output data with cross-covariance boundscited by 1
- 2022Data-driven Output-feedback Predictive Control: Unknown Plant's Order and Measurement Noisecited by 1
- 2022Data-Driven Stabilizing and Robust Control of Discrete-Time Linear Systems with Error in Variablescited by 1
- 2022Superstabilizing Control of Discrete-Time ARX Models under Error in Variablescited by 1
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.