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Composing MPC with LQR and Neural Network for Amortized Efficiency and Stable Control
[article]
2022
arXiv
pre-print
Model predictive control (MPC) is a powerful control 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 magnitude. Nevertheless, explicit MPC often requires expensive pre-computation and does
arXiv:2112.07238v3
fatcat:ioxopcvmzrdzlmiptuawyj54ca