The Koopman Operator in Systems and Control: Theory, Numerics, and Applications

Alexandre Mauroy, Igor Mezić, Yoshihiko Susuki

Research output: Book/Report/JournalBook

Abstract

This book provides a broad overview of state-of-the-art research at the intersection of the Koopman operator theory and control theory. It also reviews novel theoretical results obtained and efficient numerical methods developed within the framework of Koopman operator theory.
The contributions discuss the latest findings and techniques in several areas of control theory, including model predictive control, optimal control, observer design, systems identification and structural analysis of controlled systems, addressing both theoretical and numerical aspects and presenting open research directions, as well as detailed numerical schemes and data-driven methods. Each contribution addresses a specific problem. After a brief introduction of the Koopman operator framework, including basic notions and definitions, the book explores numerical methods, such as the dynamic mode decomposition (DMD) algorithm and Arnoldi-based methods, which are used to represent the operator in a finite-dimensional basis and to compute its spectral properties from data. The main body of the book is divided into three parts:

theoretical results and numerical techniques for observer design, synthesis analysis, stability analysis, parameter estimation, and identification;
data-driven techniques based on DMD, which extract the spectral properties of the Koopman operator from data for the structural analysis of controlled systems; and
Koopman operator techniques with specific applications in systems and control, which range from heat transfer analysis to robot control.

A useful reference resource on the Koopman operator theory for control theorists and practitioners, the book is also of interest to graduate students, researchers, and engineers looking for an introduction to a novel and comprehensive approach to systems and control, from pure theory to data-driven methods.
Original languageEnglish
PublisherSpringer
Number of pages559
Volume484
Edition1
ISBN (Electronic)978-3-030-35713-9
ISBN (Print)978-3-030-35712-2
DOIs
Publication statusAccepted/In press - 2019

Publication series

NameLecture Notes in Control and Information Sciences

Fingerprint

Control theory
Mathematical operators
Structural analysis
Numerical methods
Identification (control systems)
Decomposition
Model predictive control
Parameter estimation
Robots
Students
Heat transfer
Engineers

Cite this

Mauroy, A., Mezić, I., & Susuki, Y. (Accepted/In press). The Koopman Operator in Systems and Control: Theory, Numerics, and Applications. (1 ed.) (Lecture Notes in Control and Information Sciences). Springer. https://doi.org/10.1007/978-3-030-35713-9
Mauroy, Alexandre ; Mezić, Igor ; Susuki, Yoshihiko. / The Koopman Operator in Systems and Control : Theory, Numerics, and Applications. 1 ed. Springer, 2019. 559 p. (Lecture Notes in Control and Information Sciences).
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Mauroy, A, Mezić, I & Susuki, Y 2019, The Koopman Operator in Systems and Control: Theory, Numerics, and Applications. Lecture Notes in Control and Information Sciences, vol. 484, 1 edn, Springer. https://doi.org/10.1007/978-3-030-35713-9

The Koopman Operator in Systems and Control : Theory, Numerics, and Applications. / Mauroy, Alexandre; Mezić, Igor; Susuki, Yoshihiko.

1 ed. Springer, 2019. 559 p. (Lecture Notes in Control and Information Sciences).

Research output: Book/Report/JournalBook

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AB - This book provides a broad overview of state-of-the-art research at the intersection of the Koopman operator theory and control theory. It also reviews novel theoretical results obtained and efficient numerical methods developed within the framework of Koopman operator theory.The contributions discuss the latest findings and techniques in several areas of control theory, including model predictive control, optimal control, observer design, systems identification and structural analysis of controlled systems, addressing both theoretical and numerical aspects and presenting open research directions, as well as detailed numerical schemes and data-driven methods. Each contribution addresses a specific problem. After a brief introduction of the Koopman operator framework, including basic notions and definitions, the book explores numerical methods, such as the dynamic mode decomposition (DMD) algorithm and Arnoldi-based methods, which are used to represent the operator in a finite-dimensional basis and to compute its spectral properties from data. The main body of the book is divided into three parts: theoretical results and numerical techniques for observer design, synthesis analysis, stability analysis, parameter estimation, and identification; data-driven techniques based on DMD, which extract the spectral properties of the Koopman operator from data for the structural analysis of controlled systems; and Koopman operator techniques with specific applications in systems and control, which range from heat transfer analysis to robot control.A useful reference resource on the Koopman operator theory for control theorists and practitioners, the book is also of interest to graduate students, researchers, and engineers looking for an introduction to a novel and comprehensive approach to systems and control, from pure theory to data-driven methods.

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Mauroy A, Mezić I, Susuki Y. The Koopman Operator in Systems and Control: Theory, Numerics, and Applications. 1 ed. Springer, 2019. 559 p. (Lecture Notes in Control and Information Sciences). https://doi.org/10.1007/978-3-030-35713-9