5 papers
Co-Optimization of EV Charging Control and Incentivization for Enhanced Power System Stability
Amit Kumer Podder, Tomonori Sadamoto, Aranya Chakrabortty
We study how high charging rate demands from electric vehicles (EVs) in a power distribution grid may collectively cause poor dynamic performance, and propose a price incentivizati…
Artificial Intelligence based Approach for Identification and Mitigation of Cyber-Attacks in Wide-Area Control of Power Systems
Jishnudeep Kar, Aranya Chakrabortty
We propose a generative adversarial network (GAN) based deep learning method that serves the dual role of both identification and mitigation of cyber-attacks in wide-area damping c…
Reinforcement Learning-based Control of Nonlinear Systems using Carleman Approximation: Structured and Unstructured Designs
Jishnudeep Kar, He Bai, Aranya Chakrabortty
We develop data-driven reinforcement learning (RL) control designs for input-affine nonlinear systems. We use Carleman linearization to express the state-space representation of th…
Asynchronous Distributed Reinforcement Learning for LQR Control via Zeroth-Order Block Coordinate Descent
Gangshan Jing, He Bai, Jemin George +2
Recently introduced distributed zeroth-order optimization (ZOO) algorithms have shown their utility in distributed reinforcement learning (RL). Unfortunately, in the gradient estim…
Distributed Multi-Agent Reinforcement Learning Based on Graph-Induced Local Value Functions
Gangshan Jing, He Bai, Jemin George +2
Achieving distributed reinforcement learning (RL) for large-scale cooperative multi-agent systems (MASs) is challenging because: (i) each agent has access to only limited informati…