Learning, fast and slow: a two-fold data-based model adaptation algorithm for processes under varying operating conditions

arXiv:2507.12187 · eess.SY, cs.SY · Submitted 2025-07-16 · Read on arXiv

eess.SY, cs.SY

Submitted: 2025-07-16

Updated: 2026-09-17

Terminology

Adaptation — 22× in this paper · explained in 1 episode
Ensemble Learning — 14× in this paper · explained in 2 episodes
Accuracy — 12× in this paper · explained in 1 episode
Benchmark — 12× in this paper · explained in 2 episodes
Catastrophic Forgetting — 4× in this paper · explained in 5 episodes
Continual Learning — 3× in this paper · explained in 2 episodes
Clustering — 2× in this paper · explained in 2 episodes
Computational overhead — 2× in this paper · explained in 2 episodes
European Control Conference — 2× in this paper
Meta-learning — 2× in this paper · explained in 2 episodes
Active Learning — 1× in this paper · explained in 6 episodes
Aleatoric Uncertainty — 1× in this paper · explained in 5 episodes
Alignment — 1× in this paper · explained in 1 episode
Bayesian Inference — 1× in this paper · explained in 5 episodes
Cooperation — 1× in this paper · explained in 2 episodes
Core — 1× in this paper · explained in 2 episodes
Digital Twin — 1× in this paper · explained in 5 episodes
Fidelity — 1× in this paper · explained in 2 episodes
Mixture of Experts — 1× in this paper · explained in 2 episodes
Model Predictive Control (MPC) — 1× in this paper · explained in 5 episodes
Online Adaptation — 1× in this paper · explained in 3 episodes
Physical Constraints — 1× in this paper · explained in 7 episodes
System Identification — 1× in this paper · explained in 3 episodes
Transfer Learning — 1× in this paper · explained in 10 episodes
Verification — 1× in this paper · explained in 2 episodes

Terminology

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