57 citations · 136 across the 36 of their papers we have counts for
41 papers
Co-Optimization of Scheduling, Control, and Incentivization of Electric Vehicles for Improving Power System Stability
Amit Kumer Podder, Tomonori Sadamoto, Aranya Chakrabortty
We present a finite-horizon, greedy heuristic-based co-optimization and optimal control framework that jointly determines the optimized charging rates, charging times, and an optim…
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…
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…
Equilibrium-Independent Passivity of Power Systems: A Link Between Classical and Two-Axis Synchronous Generator Models
Takayuki Ishizaki, Taku Nishino, Aranya Chakrabortty
We study the equilibrium-independent (EI) passivity of a nonlinear power system composed of two-axis generator models. The model of our interest consists of a feedback inter-connec…
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…
Robust and Scalable Game-theoretic Security Investment Methods for Voltage Stability of Power Systems
Lu An, Pratishtha Shukla, Aranya Chakrabortty +1
We develop investment approaches to secure electric power systems against load attacks where a malicious intruder (the attacker) covertly changes reactive power setpoints of loads…
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…
Distributed Cooperative Multi-Agent Reinforcement Learning with Directed Coordination Graph
Gangshan Jing, He Bai, Jemin George +2
Existing distributed cooperative multi-agent reinforcement learning (MARL) frameworks usually assume undirected coordination graphs and communication graphs while estimating a glob…
Hierarchical Frequency and Voltage Control using Prioritized Utilization of Inverter Based Resources
Rahul Chakraborty, Aranya Chakrabortty, Evangelos Farantatos +3
We propose a novel hierarchical frequency and voltage control design for multi-area power system integrated with inverter-based resources (IBRs). The design is based on the idea of…
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…
Designing Optimal Key Lengths and Control Laws for Encrypted Control Systems based on Sample Identifying Complexity and Deciphering Time
Kaoru Teranishi, Tomonori Sadamoto, Aranya Chakrabortty +1
In the state-of-the-art literature on cryptography and control theory, there has been no systematic methodology of constructing cyber-physical systems that can achieve desired cont…
Learning Distributed Stabilizing Controllers for Multi-Agent Systems
Gangshan Jing, He Bai, Jemin George +2
We address the problem of model-free distributed stabilization of heterogeneous multi-agent systems using reinforcement learning (RL). Two algorithms are developed. The first algor…
A Robust Stackelberg Game for Cyber-Security Investment in Networked Control Systems
Pratishtha Shukla, Lu An, Aranya Chakrabortty +1
We present a resource-planning game for cyber-security of networked control systems (NCS). The NCS is assumed to be operating in closed-loop using a linear state-feedback $\mathcal…
Optimal Co-Designs of Communication and Control in Bandwidth-Constrained Cyber-Physical Systems
Nandini Negi, Aranya Chakrabortty
We address the problem of sparsity-promoting optimal control of cyber-physical systems (CPSs) in the presence of communication delays. The delays are categorized into two types - n…
Decomposability and Parallel Computation of Multi-Agent LQR
Gangshan Jing, He Bai, Jemin George +1
Individual agents in a multi-agent system (MAS) may have decoupled open-loop dynamics, but a cooperative control objective usually results in coupled closed-loop dynamics thereby m…
Model-Free Optimal Control of Linear Multi-Agent Systems via Decomposition and Hierarchical Approximation
Gangshan Jing, He Bai, Jemin George +1
Designing the optimal linear quadratic regulator (LQR) for a large-scale multi-agent system (MAS) is time-consuming since it involves solving a large-size matrix Riccati equation.…
Hierarchical Control of Multi-Agent Systems using Online Reinforcement Learning
He Bai, Jemin George, Aranya Chakrabortty
We propose a new reinforcement learning based approach to designing hierarchical linear quadratic regulator (LQR) controllers for heterogeneous linear multi-agent systems with unkn…
A Stackelberg Security Investment Game for Voltage Stability of Power Systems
Lu An, Aranya Chakrabortty, Alexandra Duel-Hallen
We formulate a Stackelberg game between an attacker and a defender of a power system. The attacker attempts to alter the load setpoints of the power system covertly and intelligent…
Reduced-Dimensional Reinforcement Learning Control using Singular Perturbation Approximations
Sayak Mukherjee, He Bai, Aranya Chakrabortty
We present a set of model-free, reduced-dimensional reinforcement learning (RL) based optimal control designs for linear time-invariant singularly perturbed (SP) systems. We first…
Co-Design of Delays and Sparse Controllers for Bandwidth-Constrained Cyber-Physical Systems
Nandini Negi, Aranya Chakrabortty
We address the problem of sparsity-promoting optimal control of cyber-physical systems with feedback delays. The delays are categorized into two classes - namely, intra-layer delay…
Efficient Algorithms for Eigensystem Realization using Randomized SVD
Rachel Minster, Arvind K. Saibaba, Jishnudeep Kar +1
Eigensystem Realization Algorithm (ERA) is a data-driven approach for subspace system identification and is widely used in many areas of engineering. However, the computational cos…
Fast Online Reinforcement Learning Control using State-Space Dimensionality Reduction
Tomonori Sadamoto, Aranya Chakrabortty, Jun-ichi Imura
In this paper, we propose a fast reinforcement learning (RL) control algorithm that enables online control of large-scale networked dynamic systems. RL is an effective way of desig…
Game-Theoretic Mixed Control with Sparsity Constraint for Multi-agent Networked Control Systems
Feier Lian, Aranya Chakrabortty, Alexandra Duel-Hallen
Multi-agent networked control systems (NCSs) are often subject to model uncertainty and are limited by large communication cost, associated with feedback of data between the system…
Sparsity-Promoting Optimal Control of Cyber-Physical Systems over Shared Communication Networks
Nandini Negi, Aranya Chakrabortty
Recent years have seen several new directions in the design of sparse control of cyber-physical systems (CPSs) driven by the objective of reducing communication cost. One common as…