A Survey on Machine Learning Applied to Dynamic Physical Systems
arXiv:2009.09719
Abstract
This survey is on recent advancements in the intersection of physical modeling and machine learning. We focus on the modeling of nonlinear systems which are closer to electric motors. Survey on motor control and fault detection in operation of electric motors has been done.
arXiv commentarXiv admin note: submission has been withdrawn by arXiv administrators due to inappropriate text overlap with external source
References in corpus (6)
- Theory-guided Data Science: A New Paradigm for Scientific Discovery from Data
- Deep learning for universal linear embeddings of nonlinear dynamics
- Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
- Learning New Physics from a Machine
- Analyzing Inverse Problems with Invertible Neural Networks
- Nonlinear Systems Identification Using Deep Dynamic Neural Networks