Algorithms for data-driven H∞-norm estimation 2019 (English)In: Data-Driven Modeling, Filtering and Control, Institution of Engineering and Technology (IET) , 2019, p. 145-163Chapter in book (Other academic)

Abstract [en]

In this chapter, the problem of estimating in a model-free manner the H∞ normofa linear dynamic system is discussed at a tutorial level. Two recently developed methods for addressing this problem are presented, namely the power iterations method and a class of multi-armed bandit (MAB) algorithms. Due to reasons of space, many details are omitted, but references are provided to complement this exposition.

Place, publisher, year, edition, pages

Institution of Engineering and Technology (IET) , 2019. p. 145-163

Keywords [en]

Data-driven H∞-norm estimation, H∞ control, Interpolation and function approximation (numerical analysis), Iterative methods, Linear dynamic system, Linear systems, MAB algorithm, Multiarmed bandit algorithms, Norm estimation, Optimal control, Optimisation techniques, Other topics in statistics

National Category

Computer graphics and computer vision

Identifiers

URN: urn:nbn:se:kth:diva-312953DOI: 10.1049/pbce123e_ch8Scopus ID: 2-s2.0-85118066605OAI: oai:DiVA.org:kth-312953DiVA, id: diva2:1661183

Note

QC 20220525

Part of book ISBN 9781785617126

Available from: 2022-05-25 Created: 2022-05-25 Last updated: 2025-02-07Bibliographically approved

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Rojas, Cristian R.Müller, Matias I.

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Rojas, Cristian R.Müller, Matias I.

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Decision and Control Systems (Automatic Control)

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Computer graphics and computer vision

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