1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.RO2026
Geometric Distributional Control: Learning Progress with Partial Structural Knowledge
Tong Wu
Real-time control often sits between two limiting regimes. Predictive optimization and model-based control are powerful when dynamics, parameters, objectives, and online planning m…
eess.SY2023★ 1 cited
Constrained Reinforcement Learning for Predictive Control in Real-Time Stochastic Dynamic Optimal Power Flow
Tong Wu, Anna Scaglione, Daniel Arnold
Deep Reinforcement Learning (DRL) has become a popular method for solving control problems in power systems. Conventional DRL encourages the agent to explore various policies encod…
eess.SY2022★ 1 cited
Spatio-Temporal Graph Convolutional Neural Networks for Physics-Aware Grid Learning Algorithms
Tong Wu, Ignacio Losada Carreno, Anna Scaglione +1
This paper proposes a model-free Volt-VAR control (VVC) algorithm via the spatio-temporal graph ConvNet-based deep reinforcement learning (STGCN-DRL) framework, whose goal is to co…