Data-Driven Multi-Modal Learning Model Predictive Control
<|reference_start|>Data-Driven Multi-Modal Learning Model Predictive Control: We present a Learning Model Predictive Controller (LMPC) for multi-modal systems performing iterative control tasks. Assuming availability of historical data, our goal is to design a data-driven control policy for the multi-modal system where the current mode is unknown. First, we propose a novel method to select local data for constructing affine time-varying (ATV) models of a multi-modal system in the context of LMPC. Then we present how to build a sampled safe set from multi-modal historical data. We demonstrate the effectiveness of our method through simulation results of automated driving on a friction-varying track.<|reference_end|>
@article{kopp2024data-driven,
    title={Data-Driven Multi-Modal Learning Model Predictive Control},
    author={Fionna B. Kopp and Francesco Borrelli},
    journal={arXiv preprint arXiv:2407.06313},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.06313},
    primaryClass={eess.SY cs.SY}
}