1 citations · 1 across the 7 of their papers we have counts for
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Goal-oriented safe active learning for predictive control using Bayesian recurrent neural networks
Laura Boca de Giuli, Alessio La Bella, Manish Prajapat +4
A key challenge in learning-based model predictive control (MPC) is to collect informative data online for model adaptation while ensuring safety and without penalising control per…
Gaussian processes for dynamics learning in model predictive control
Anna Scampicchio, Elena Arcari, Amon Lahr +1
Due to its state-of-the-art estimation performance complemented by rigorous and non-conservative uncertainty bounds, Gaussian process regression is a popular tool for enhancing dyn…
On the role of the signature transform in nonlinear systems and data-driven control
Anna Scampicchio, Melanie N. Zeilinger
Classic control techniques typically rely on a model of the system's response to external inputs, which is difficult to obtain from first principles especially if the unknown dynam…