Learning Model Predictive Control Parameters via Bayesian Optimization for Battery Fast Charging

arXiv:2404.06125v1 Announce Type: cross
Abstract: Tuning parameters in model predictive control (MPC) presents significant challenges, particularly when there is a notable discrepancy between the controller's predictions and the actual behavior of the closed-loop plant. This mismatch may stem from factors like substantial model-plant differences, limited prediction horizons that do not cover the entire time of interest, or unforeseen system disturbances. Such mismatches can jeopardize both performance and safety, including constraint satisfaction. Traditional methods address this issue by modifying the finite …

abstract arxiv battery bayesian behavior challenges charging control cs.lg cs.sy differences eess.sy loop mpc optimization parameters prediction predictions predictive stem type via