A Fast Smoothing-Based Algorithm to Generate l-Norm Constrained Signals for Multivariable Experiment Design

Nic Dirkx*, Marcel Bosselaar, Tom Oomen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Handling peak amplitude constraints, or equivalently l∞-norm constraints, is an important application demand in experiment design for system identification. The aim of this letter is to present a method for the design of excitation signals with prescribed power spectrum under l∞-norm constraints for systems with many inputs and outputs. The method exploits an exponential smoothing function in an iterative algorithm. Fast convergence is achieved by a computationally efficient construction of the gradient and the Hessian matrix. Experimental results show excellent convergence behavior that overcomes local minima, while significantly reducing computation time compared to existing techniques.

Original languageEnglish
Pages (from-to)1784-1789
JournalIEEE Control Systems Letters
Volume6
DOIs
Publication statusPublished - 2022

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Crest-factor optimization
  • experiment design
  • system identification

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