A goal-oriented safe active learning algorithm embedded in MPC with Bayesian RNNs delivers theoretical guarantees of safety and finite-time exploration termination while achieving near-optimal economic performance in simulations.
(2018), ‘Stochastic model predictive control with active uncertainty learning: A survey on dual control’,Annual Reviews in Control45, 107–117
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Goal-oriented safe active learning for predictive control using Bayesian recurrent neural networks
A goal-oriented safe active learning algorithm embedded in MPC with Bayesian RNNs delivers theoretical guarantees of safety and finite-time exploration termination while achieving near-optimal economic performance in simulations.