1 citations · 1 across the 1 of their papers we have counts for
3 papers
QRnet: optimal regulator design with LQR-augmented neural networks
Tenavi Nakamura-Zimmerer, Qi Gong, Wei Kang
In this paper we propose a new computational method for designing optimal regulators for high-dimensional nonlinear systems. The proposed approach leverages physics-informed machin…
Density Propagation with Characteristics-based Deep Learning
Tenavi Nakamura-Zimmerer, Daniele Venturi, Qi Gong +1
Uncertainty propagation in nonlinear dynamic systems remains an outstanding problem in scientific computing and control. Numerous approaches have been developed, but are limited in…
Adaptive Deep Learning for High-Dimensional Hamilton-Jacobi-Bellman Equations
Tenavi Nakamura-Zimmerer, Qi Gong, Wei Kang
Computing optimal feedback controls for nonlinear systems generally requires solving Hamilton-Jacobi-Bellman (HJB) equations, which are notoriously difficult when the state dimensi…