activity
20192022
most citedAdaptive Deep Learning for High-Dimensional Hamilton-Jacobi-Bellman Equations

105 citations · 185 across the 7 of their papers we have counts for

collaborators

7 papers

math.OC2022

An Actor Critic Method for Free Terminal Time Optimal Control

Evan Burton, Tenavi Nakamura-Zimmerer, Qi Gong +1

Optimal control problems with free terminal time present many challenges including nonsmooth and discontinuous control laws, irregular value functions, many local optima, and the c…

math.OC2022★ 15 cited

Neural Network Optimal Feedback Control with Guaranteed Local Stability

Tenavi Nakamura-Zimmerer, Qi Gong, Wei Kang

Recent research shows that supervised learning can be an effective tool for designing near-optimal feedback controllers for high-dimensional nonlinear dynamic systems. But the beha…

math.OC2021★ 7 cited

Neural network optimal feedback control with enhanced closed loop stability

Tenavi Nakamura-Zimmerer, Qi Gong, Wei Kang

Recent research has shown that supervised learning can be an effective tool for designing optimal feedback controllers for high-dimensional nonlinear dynamic systems. But the behav…

math.OC2020★ 41 cited

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…

math.DS2020★ 16 cited

Algorithms of Data Development For Deep Learning and Feedback Design

Wei Kang, Qi Gong, Tenavi Nakamura-Zimmerer

Recent research reveals that deep learning is an effective way of solving high dimensional Hamilton-Jacobi-Bellman equations. The resulting feedback control law in the form of a ne…

math.DS2019★ 1 cited

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…

math.OC2019★ 105 cited

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…