36 citations · 44 across the 7 of their papers we have counts for
7 papers
Global Description of Flutter Dynamics via Koopman Theory
Jiwoo Song, Daning Huang
This paper presents a novel parametrization approach for aeroelastic systems utilizing Koopman theory, specifically leveraging the Koopman Bilinear Form (KBF) model. To address the…
Modal Analysis of Spatiotemporal Data via Multivariate Gaussian Process Regression
Jiwoo Song, Daning Huang
Modal analysis has become an essential tool to understand the coherent structure of complex flows. The classical modal analysis methods, such as dynamic mode decomposition (DMD) an…
Learning Koopman Operators with Control Using Bi-level Optimization
Daning Huang, Muhammad Bayu Prasetyo, Yin Yu +1
The accurate modeling and control of nonlinear dynamical effects are crucial for numerous robotic systems. The Koopman formalism emerges as a valuable tool for linear control desig…
PyPose: A Library for Robot Learning with Physics-based Optimization
Chen Wang, Dasong Gao, Kuan Xu +34
Deep learning has had remarkable success in robotic perception, but its data-centric nature suffers when it comes to generalizing to ever-changing environments. By contrast, physic…
Physics-Infused Reduced Order Modeling of Aerothermal Loads for Hypersonic Aerothermoelastic Analysis
Carlos Vargas Venegas, Daning Huang
This paper presents a novel physics-infused reduced-order modeling (PIROM) methodology for efficient and accurate modeling of non-linear dynamical systems. The PIROM consists of a…
Modularized Bilinear Koopman Operator for Modeling and Predicting Transients of Microgrids
Xinyuan Jiang, Yan Li, Daning Huang
Modularized Koopman Bilinear Form (M-KBF) is presented to model and predict the transient dynamics of microgrids in the presence of disturbances. As a scalable data-driven approach…
PIDGeuN: Graph Neural Network-Enabled Transient Dynamics Prediction of Networked Microgrids Through Full-Field Measurement
Yin Yu, Xinyuan Jiang, Daning Huang +1
A Physics-Informed Dynamic Graph Neural Network (PIDGeuN) is presented to accurately, efficiently and robustly predict the nonlinear transient dynamics of microgrids in the presenc…