UDUC: An Uncertainty-driven Approach for Learning-based Robust Control

arXiv:2405.02598v1 Announce Type: new
Abstract: Learning-based techniques have become popular in both model predictive control (MPC) and reinforcement learning (RL). Probabilistic ensemble (PE) models offer a promising approach for modelling system dynamics, showcasing the ability to capture uncertainty and scalability in high-dimensional control scenarios. However, PE models are susceptible to mode collapse, resulting in non-robust control when faced with environments slightly different from the training set. In this paper, we introduce the $\textbf{u}$ncertainty-$\textbf{d}$riven rob$\textbf{u}$st $\textbf{c}$ontrol (UDUC) loss as an alternative …

abstract arxiv become control cs.lg dynamics ensemble however modelling mpc popular predictive reinforcement reinforcement learning robust scalability type uncertainty