Methods for solving optimal control problems for bilinear systems. This package also contains the JDMD algorithm for learning bilinear koopman models with jacobian-regularized dynamic mode decomposition.
If you use BilinearControl.jl and the JDMD algorithm as part of your research, teaching, or other activities, we would be grateful if you could cite our work:
[1] B. E. Jackson, J. H. Lee, K. Tracy, and Z. Manchester, “Data-Efficient Model Learning for Control with Jacobian-Regularized Dynamic Mode Decomposition,” presented at the Conference on Robot Learning (CoRL), Aukland, Dec. 2022. doi: 10.48550/ARXIV.2212.07885.
@inproceedings{jackson_data-efficient_2022,
address = {Aukland},
title = {Data-{Efficient} {Model} {Learning} for {Control} with {Jacobian}-{Regularized} {Dynamic} {Mode} {Decomposition}},
copyright = {arXiv.org perpetual, non-exclusive license},
url = {https://arxiv.org/abs/2212.07885},
doi = {10.48550/ARXIV.2212.07885},
language = {en},
author = {Jackson, Brian E and Lee, Jeong Hun and Tracy, Kevin and Manchester, Zachary},
month = dec,
year = {2022},
}