A Fast Smoothing-Based Algorithm to Generate l<sub>∞</sub>-Norm Constrained Signals for Multivariable Experiment Design

Journal article (2022)

Authors

Nic Dirkx ASML
Marcel Bosselaar Eindhoven University of Technology
T.A.E. Oomen Eindhoven University of Technology, Team Jan-Willem van Wingerden - Mechanical, Maritime and Materials Engineering
Research Group
Team Jan-Willem van Wingerden (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2022 Nic Dirkx, Marcel Bosselaar, T.A.E. Oomen
DOI
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https://doi.org/10.1109/LCSYS.2021.3133655
System identification Experiment design Crest-factor optimization
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Published Date

2022

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Jan-Willem van Wingerden

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.