AI RESEARCH
On Building Myopic MPC Policies using Supervised Learning
arXiv CS.LG
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ArXi:2401.12546v3 Announce Type: replace The application of supervised learning techniques in combination with model predictive control (MPC) has recently generated significant interest, particularly in the area of approximate explicit MPC, where function approximators like deep neural networks are used to learn the MPC policy via optimal state-action pairs generated offline.