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Found 5 papers, 2 papers with code
Neural Network Optimal Feedback Control with Guaranteed Local Stability
The proposed architectures are compared against standard neural network feedback controllers through numerical simulations of two high-dimensional nonlinear optimal control problems: stabilization of an unstable Burgers-type partial differential equation, and altitude and course tracking for an unmanned aerial vehicle.
Neural network optimal feedback control with enhanced closed loop stability
In this paper we use numerical simulations to demonstrate that typical test accuracy metrics do not effectively capture the ability of an NN controller to stabilize a system.
QRnet: optimal regulator design with LQR-augmented neural networks
In this paper we propose a new computational method for designing optimal regulators for high-dimensional nonlinear systems.
BIG-bench Machine Learning
Physics-informed machine learning
Density Propagation with Characteristics-based Deep Learning
Uncertainty propagation in nonlinear dynamic systems remains an outstanding problem in scientific computing and control.
Adaptive Deep Learning for High-Dimensional Hamilton-Jacobi-Bellman Equations
In this paper, we propose a data-driven method to approximate semi-global solutions to HJB equations for general high-dimensional nonlinear systems and compute candidate optimal feedback controls in real-time.
