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REDPC: A Real-time Efficient approximate DeePC

Python version

The code is tested with Python 3.10

Installation

pip install -r requirements.txt
git clone git@github.com:zhou-yh19/PyDeePC.git
cd PyDeePC
pip install -e .

Code structure

  • src/modules: PyTorch modules for approximating the scoring function
  • src/scripts: Scripts for data augmentation, and computing different scoring function
  • src/utils: Utility functions (customized PyTorch operations, tensor operations, etc.)
  • src/train.py: Training script for the scoring function
  • src/grid_train_one_gpu.py: Training script for the scoring function on a single GPU
  • experiments: Sample scripts for running experiments
  • test: julia scripts for testing solver

License

The project is released under the MIT license. See LICENSE for details.

Part of the project is modified from PyDeePC

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Learning-Based Efficient Approximation of Data-Enabled Predictive Control

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