Controller Synthesis for Input-State Data With Measurement Errors

Andrea Bisoffi*, Lidong Li, Claudio De Persis, Nima Monshizadeh

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

11 Downloads (Pure)

Abstract

We consider the problem of designing a state-feedback controller for a linear system, based only on noisy input-state data. We focus on input-state data corrupted by measurement errors, which, albeit less investigated, are as relevant as process disturbances in applications. For energy and instantaneous bounds on these measurement errors, we derive linear matrix inequalities for controller design where the one for the energy bound is equivalent to robust stabilization of all systems consistent with the noisy data points via a common Lyapunov function.

Original languageEnglish
Pages (from-to)1571 - 1576
Number of pages6
JournalIEEE Control Systems Letters
Volume8
Early online date16-May-2024
DOIs
Publication statusPublished - Jul-2024

Keywords

  • Data-driven control
  • linear matrix inequalities
  • Linear systems
  • Measurement errors
  • measurement errors
  • Measurement uncertainty
  • Noise
  • Noise measurement
  • robust control
  • Sufficient conditions
  • Symmetric matrices
  • uncertain systems

Fingerprint

Dive into the research topics of 'Controller Synthesis for Input-State Data With Measurement Errors'. Together they form a unique fingerprint.

Cite this