57 citations · 213 across the 28 of their papers we have counts for
6 papers · 1 filter
Safe Reinforcement Learning for Grid Voltage Control
Thanh Long Vu, Sayak Mukherjee, Renke Huang +1
Under voltage load shedding has been considered as a standard approach to recover the voltage stability of the electric power grid under emergency conditions, yet this scheme usual…
Data-Driven Pole Placement in LMI Regions with Robustness Constraints
Sayak Mukherjee, Ramij R. Hossain
This paper proposes a robust learning methodology to place the closed-loop poles in desired convex regions in the complex plane. We considered the system state and input matrices t…
On the Stochastic Stability of Deep Markov Models
Ján Drgoňa, Sayak Mukherjee, Jiaxin Zhang +2
Deep Markov models (DMM) are generative models that are scalable and expressive generalization of Markov models for representation, learning, and inference problems. However, the f…
Barrier Function-based Safe Reinforcement Learning for Emergency Control of Power Systems
Thanh Long Vu, Sayak Mukherjee, Renke Huang +1
Under voltage load shedding has been considered as a standard and effective measure to recover the voltage stability of the electric power grid under emergency and severe condition…
A Secure Learning Control Strategy via Dynamic Camouflaging for Unknown Dynamical Systems under Attacks
Sayak Mukherjee, Veronica Adetola
This paper presents a secure reinforcement learning (RL) based control method for unknown linear time-invariant cyber-physical systems (CPSs) that are subjected to compositional at…
Scalable Voltage Control using Structure-Driven Hierarchical Deep Reinforcement Learning
Sayak Mukherjee, Renke Huang, Qiuhua Huang +2
This paper presents a novel hierarchical deep reinforcement learning (DRL) based design for the voltage control of power grids. DRL agents are trained for fast, and adaptive select…