• Corpus ID: 250264149

Composing MPC with LQR and Neural Network for Amortized Efficiency and Stable Control

@inproceedings{Wu2021ComposingMW,
  title={Composing MPC with LQR and Neural Network for Amortized Efficiency and Stable Control},
  author={Fangyu Wu and Guanhua Wang and Siyuan Zhuang and Kehan Wang and Alexander Keimer and Ionut Alexandru Stoica and Alexandre M. Bayen},
  year={2021}
}
—Model predictive control (MPC) is a powerful con- trol method that handles dynamical systems with constraints. However, solving MPC iteratively in real time, i.e., implicit MPC, remains a computational challenge. To address this, common solutions include explicit MPC and function approximation. Both methods, whenever applicable, may improve the computational efficiency of the implicit MPC by several orders of magni- tude. Nevertheless, explicit MPC often requires expensive pre-computation and… 

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