57 citations · 136 across the 36 of their papers we have counts for
31 papers · 1 filter
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…
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…
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…
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…
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…
A New Cyber-Secure Countermeasure for LTI systems under DoS attacks
Nilanjan Roy Chowdhury, Nandini Negi, Aranya Chakrabortty
This paper presents a new counter-measure to mitigate denial-of-service cyber-attacks in linear time-invariant (LTI) systems. We first design a sparse linear quadratic regulator (L…
Modeling and Quantifying the Impact of Wind Power Penetration on Power System Coherency
Sayak Mukherjee, Aranya Chakrabortty, Saman Babaei
This paper presents a mathematical analysis of how wind generation impacts the coherency property of power systems. Coherency arises from time-scale separation in the dynamics of s…
A Cyber-Security Investment Game for Networked Control Systems
Pratishtha Shukla, Aranya Chakrabortty, Alexandra Duel-Hallen
We formulate a resource-planning game between an attacker and a defender of a network control system. We consider the network to be operating in closed-loop with a linear quadratic…
Coordinated Control of Energy Storage in Networked Microgrids under Unpredicted Load Demands
Md Tanvir Arafat Khan, Rafael Cisneros, Aranya Chakrabortty +1
In this paper a nonlinear control design for power balancing in networked microgrids using energy storage devices is presented. Each microgrid is considered to be interfaced to the…
Sparse Wide-Area Control of Power Systems using Data-driven Reinforcement Learning
Amirhassan Fallah Dizche, Aranya Chakrabortty, Alexandra Duel-Hallen
In this paper we present an online wide-area oscillation damping control (WAC) design for uncertain models of power systems using ideas from reinforcement learning. We assume that…
Dynamic Modeling, Stability, and Control of Power Systems with Distributed Energy Resources
Tomonori Sadamoto, Aranya Chakrabortty, Takayuki Ishizaki +1
This article presents a suite of new control designs for next-generation electric smart grids. The future grid will consist of thousands of non-conventional renewable generation so…
Control Inversion: A Clustering-Based Method for Distributed Wide-Area Control of Power Systems
Nan Xue, Aranya Chakrabortty
Wide-area control (WAC) has been shown to be an effective tool for damping low-frequency oscillations in power systems. In the current state of art, WAC is challenged by two main f…
Synchronization and Aggregation of Nonlinear Power Systems with Consideration of Bus Network Structures
Petar Mlinarić, Takayuki Ishizaki, Aranya Chakrabortty +3
We study nonlinear power systems consisting of generators, generator buses, and non-generator buses. First, looking at a generator and its bus' variables jointly, we introduce a sy…