This the released code for L4DC 2025 "Safe pde boundary control with neural operators" (PDF).
The code is based on Julia and Python. It is tested with Julia v1.9.4. Check here to install Julia environment. Install NeuralOperators.jl
from here. For Python part, the code is based on PDEControlGym
, which can be installed based on doc.
Train or download the PPO and SAC models for all the environments following README.md
of PDEControlGym.
To collect data for hyperbolic environment, see Jupyter file HyperbolicPDEExample.ipynb
for details. To collect data for parabolic environment, see Jupyter file ParabolicPDEExample.ipynb
for details. To collect data for Navier-Stokes environment, see Jupyter file NS2DExample.ipynb
for details.
Check out preprocess_hyperbolic.ipynb
for data preprocessing of collected hyperbolic PDE data. Check out preprocess_parabolic.ipynb
for data preprocessing of collected parabolic PDE data. Check out preprocess_ns.ipynb
for data preprocessing of collected Navier-Stokes data.
Under hyperbolic equation, see train_hyper_all_pf.jl
for neural operator training and the Jupyter file train_cbf_hyper.ipynb
for neual BCBF training. Similarly, see train_para_all_pf.jl
to train neural operator and the Jupyter file train_cbf_parabolic.ipynb
for neual BCBF training under parabolic equation. see train_ns_all_pf.jl
to train neural operator and the Jupyter file train_cbf_ns.ipynb
for neual BCBF training under Navier-Stokes equation.
For the safety filtering over the collected trajectories, see Jupyter file test_cbf_hyper.ipynb
for hyperbolic equation, test_cbf_parabolic.ipynb
for parabolic equation, and test_cbf_ns.ipynb
for Navier-Stokes equation. For the reward and PF metric metric evaluation, see Jupyter file transportPDE/HyperbolicPDEExample.ipynb
for hyperbolic equation, Jupyter file reactionDiffusionPDE/ParabolicPDEExample.ipynb
for parabolic equation and Jupyter file NS2Dtest.ipynb
Navier-Stokes equation.
If you find the repo useful, please cite:
H. Hu and C. Liu "Safe PDE Boundary Control with Neural Operators", Learning for Dynamics & Control Conference (L4DC). PMLR, 2025
@article{hu2025safe,
title={Safe PDE Boundary Control with Neural Operators},
author={Hu, Hanjiang and Liu, Changliu},
journal={7th Annual Learning for Dynamics \& Control Conference},
year={2025}
}