Published April 30, 2024 | Version v1
Dataset Open

Supplementary Dataset for the Paper: "Parameter-Adaptive Approximate MPC: Tuning Neural-Network Controllers without Re-Training"

  • 1. ROR icon RWTH Aachen University

Description

Supplementary dataset for paper Hose, Henrik, Alexander Gräfe, and Sebastian Trimpe. "Parameter-Adaptive Approximate MPC: Tuning Neural-Network Controllers without Re-Training." arXiv preprint arXiv:2404.05835 (2024).

The code to use this dataset is publicly available at https://github.com/hshose/Adaptive-AMPC-Cartpole

The dataset contains training and testing data to train an NN controller for a standart cartpole system.

For each system, there are initial conditions as comma separated value in the `x0.txt` file, the MPC input trajectory in the `U.txt` file and the corresponding predicted state sequence in the `X.txt` file. Additionally, sensitivities (i.e. gradients dU/dtheta with respect to some system parameters theta) are provided in a file called `J.txt`.

Files

FinalAMPCPendulumDataset.zip

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