Modern Koopman theory for dynamical systems
The field of dynamical systems is being transformed by the mathematical tools and
algorithms emerging from modern computing and data science. First-principles derivations …
algorithms emerging from modern computing and data science. First-principles derivations …
Data-driven fault diagnosis for traction systems in high-speed trains: A survey, challenges, and perspectives
Recently, to ensure the reliability and safety of high-speed trains, detection and diagnosis of
faults (FDD) in traction systems have become an active issue in the transportation area over …
faults (FDD) in traction systems have become an active issue in the transportation area over …
Transfer learning-motivated intelligent fault diagnosis designs: A survey, insights, and perspectives
Over the last decade, transfer learning has attracted a great deal of attention as a new
learning paradigm, based on which fault diagnosis (FD) approaches have been intensively …
learning paradigm, based on which fault diagnosis (FD) approaches have been intensively …
[图书][B] Dynamic mode decomposition: data-driven modeling of complex systems
The integration of data and scientific computation is driving a paradigm shift across the
engineering, natural, and physical sciences. Indeed, there exists an unprecedented …
engineering, natural, and physical sciences. Indeed, there exists an unprecedented …
Projection-based model reduction: Formulations for physics-based machine learning
This paper considers the creation of parametric surrogate models for applications in science
and engineering where the goal is to predict high-dimensional output quantities of interest …
and engineering where the goal is to predict high-dimensional output quantities of interest …
Model reduction for flow analysis and control
CW Rowley, STM Dawson - Annual Review of Fluid Mechanics, 2017 - annualreviews.org
Advances in experimental techniques and the ever-increasing fidelity of numerical
simulations have led to an abundance of data describing fluid flows. This review discusses a …
simulations have led to an abundance of data describing fluid flows. This review discusses a …
Dynamic mode decomposition with control
We develop a new method which extends dynamic mode decomposition (DMD) to
incorporate the effect of control to extract low-order models from high-dimensional, complex …
incorporate the effect of control to extract low-order models from high-dimensional, complex …
Fault detection for nonlinear dynamic systems with consideration of modeling errors: A data-driven approach
This article is concerned with data-driven realization of fault detection (FD) for nonlinear
dynamic systems. In order to identify and parameterize nonlinear Hammerstein models …
dynamic systems. In order to identify and parameterize nonlinear Hammerstein models …
Generalizing Koopman theory to allow for inputs and control
We develop a new generalization of Koopman operator theory that incorporates the effects
of inputs and control. Koopman spectral analysis is a theoretical tool for the analysis of …
of inputs and control. Koopman spectral analysis is a theoretical tool for the analysis of …
Real-time implementation of fault-tolerant control systems with performance optimization
In this paper, two online schemes for an integrated design of fault-tolerant control (FTC)
systems with application to Tennessee Eastman (TE) benchmark are proposed. Based on …
systems with application to Tennessee Eastman (TE) benchmark are proposed. Based on …