000			04922nam a22004455i 4500
999			_c119359 _d119359
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003			ES-MaUEC
005			20230102113944.0
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007			cr nn nnnaamaa
008			200222s2020 gw | s |||| 0|eng d
020			_a9783030357139
024	7		_a10.1007/978-3-030-35713-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA329 _b2020 EB
245	1	4	_aThe Koopman Operator in Systems and Control _bConcepts, Methodologies, and Applications _cedited by Alexandre Mauroy, Igor Mezić, Yoshihiko Susuki.
250			_aFirst edition 2020.
264		1	_aCham _bSpringer International Publishing : _bImprint: Springer _c2020.
300			_a1 recurso en línea (XXIII, 556 páginas) _b138 ilustraciones, 85 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aArchivo de texto _bPDF
490	0		_aLecture Notes in Control and Information Sciences _x0170-8643 _v484
490	0		_aIntelligent Technologies and Robotics (Springer-42732)
505	0		_aPart I: Control Design, Observation, and Identification -- Linear Observer Synthesis for Nonlinear Systems -- Linear Predictors for Nonlinear Dynamical Systems -- Global Stability Analysis -- Pulse-based Optimal Control -- Parameter Estimation and Identification of Nonlinear Systems -- Koopman Spectrum and Stability of Cascaded Dynamical Systems -- Open and Closed Loop Control of PDEs via Switched Systems and Koopman operator based reduced order models -- Part II: Data-Driven Analysis -- Data-driven Approximations of Dynamical Systems Operators for Control -- Operator Theoretic-based Data-driven Approach for Optimal Stabilization of Nonlinear System -- Manifold Learning for Data-Driven Dynamical Systems Analysis -- Use of Data-Driven Koopman Spectrum Computation and Delay Embedding -- Part III: Applications -- Modeling of Advective Heat Transfer in a Practical Building Atrium via Koopman Mode Decomposition -- Phase-amplitude Reduction of Limit-cycling Systems -- Exploiting Effects of Network Topology on Performance in Nonlinear Consensus Networks -- Koopman Operators in Embedded Control.
520	3		_aThis 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.
988			_aSpringer_Robotics_31032020
650		7	_2embne _aOperadores, Teoría de _9670824
700	1		_aMauroy, Alexandre _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aMezić, Igor _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aSusuki, Yoshihiko _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
710	2		_aSpringerLink (Online service)
776	0	8	_iPrinted edition: _z9783030357122
776	0	8	_iPrinted edition: _z9783030357146
776	0	8	_iPrinted edition: _z9783030357153
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-35713-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b05/2020 _dz _eh _zSI