Optimal transport for parameter identification of chaotic dynamics via invariant measures
We study an optimal transportation approach for recovering parameters in dynamical
systems with a single smoothly varying attractor. We assume that the data are not sufficient …
systems with a single smoothly varying attractor. We assume that the data are not sufficient …
Parameter inference of time series by delay embeddings and learning differentiable operators
We provide a method to identify system parameters of dynamical systems, called ID-ODE--
Inference by Differentiation and Observing Delay Embeddings. In this setting, we are given a …
Inference by Differentiation and Observing Delay Embeddings. In this setting, we are given a …
[PDF][PDF] Robust Deep Learning Algorithms for System Identification
E Negrini - 2022 - digital.wpi.edu
In this dissertation we develop mathematically-principled deep learning algorithms for
system identification. Our algorithms are completely data-driven, robust to noise and can be …
system identification. Our algorithms are completely data-driven, robust to noise and can be …
[PDF][PDF] Nonlinear Identification of a Flexible Joint Robotic Actuator Using Proprioceptive and Video Data
AWC do Lago - 2024 - maxwell.vrac.puc-rio.br
Antonio Weiller Corrêa do Lago Nonlinear Identification of a Flexible Joint Robotic Actuator Using
Proprioceptive and Video Dat Page 1 Antonio Weiller Corrêa do Lago Nonlinear Identification of …
Proprioceptive and Video Dat Page 1 Antonio Weiller Corrêa do Lago Nonlinear Identification of …
Learning neural network models for the identification and control of non linear dynamical systems
S Piazza - 2022 - politesi.polimi.it
Abstract This Thesis investigates a Model Predictive Control (MPC) method applicable in
scenarios where no prior knowledge of system dynamics equations is available. The use of …
scenarios where no prior knowledge of system dynamics equations is available. The use of …