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The Koopman Operator in Systems and Control

- Concepts, Methodologies, and Applications

Über The Koopman Operator in Systems and Control

Part 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.

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  • Sprache:
  • Englisch
  • ISBN:
  • 9783030357122
  • Einband:
  • Gebundene Ausgabe
  • Seitenzahl:
  • 556
  • Veröffentlicht:
  • 23 Februar 2020
  • Ausgabe:
  • 12020
  • Abmessungen:
  • 155x235x0 mm.
  • Gewicht:
  • 1027 g.
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Beschreibung von The Koopman Operator in Systems and Control

Part 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.

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