Description
- 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.
Table of Contents
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 Effectsof Network Topology on Performance in Nonlinear Consensus Networks.- Koopman Operators in Embedded Control.