Guaranteeing Stability in Structured Input-Output Models: With Application to System Identification

J.J. Kon, Roland Tóth, Jeroen J.M. van de Wijdeven, Marcel F. Heertjes, Tom Oomen

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Abstract

Identifying structured discrete-time linear time/parameter-varying (LPV) input-output (IO) models with global stability guarantees is a challenging problem since stability for such models is only implicitly defined through the solution of matrix inequalities (MI) in terms of the model's coefficient functions. In this paper, a structured linear IO model class is developed that results in a quadratically stable model for any choice of coefficient functions, enabling identification using standard optimization routines while guaranteeing stability. This is achieved through transforming the MI-based stability constraints in a necessary and sufficient manner, such that for any choice of transformed coefficient functions the MIs are satisfied. The developed stable LPV-IO model is employed in simulation to estimate the parameter-varying damping of mass-damper-spring system with stability guarantees, while a standard LPV-IO model results in an unstable estimate.
Original languageEnglish
Article number10550016
Pages (from-to)1565-1570
Number of pages6
JournalIEEE Control Systems Letters
Volume8
DOIs
Publication statusPublished - 2024

Keywords

  • System identification
  • stability
  • linear parameter-varying systems
  • transfer functions

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