activity
20122022
most citedMRAC-RL: A Framework for On-Line Policy Adaptation Under Parametric Model Uncertainty

5 citations · 13 across the 9 of their papers we have counts for

collaborators

14 papers

econ.GN2022

Human Behavioral Models Using Utility Theory and Prospect Theory

Anuradha M. Annaswamy, Vineet Jagadeesan Nair

Several examples of Cyber-physical human systems (CPHS) include real-time decisions from humans as a necessary building block for the successful performance of the overall system.…

math.OC2022

Accelerated Algorithms for a Class of Optimization Problems with Constraints

Anjali Parashar, Priyank Srivastava, Anuradha M. Annaswamy

This paper presents a framework to solve constrained optimization problems in an accelerated manner based on High-Order Tuners (HT). Our approach is based on reformulating the orig…

eess.SY20211 cited

DER Forecast using Privacy Preserving Federated Learning

Venkatesh Venkataramanan, Sridevi Kaza, Anuradha M. Annaswamy

With increasing penetration of Distributed Energy Resources (DERs) in grid edge including renewable generation, flexible loads, and storage, accurate prediction of distributed gene…

math.OC2021

Sensitivity Analysis of Passenger Behavioral Model for Dynamic Pricing of Shared Mobility on Demand

Vineet Jagadeesan Nair, Yue Guan, Anuradha M. Annaswamy +2

This paper provides a framework to quantify the sensitivity associated with behavioral models based on Cumulative Prospect Theory (CPT). These are used to design dynamic pricing st…

eess.SY2021

Online Policies for Real-Time Control Using MRAC-RL

Anubhav Guha, Anuradha Annaswamy

In this paper, we propose the Model Reference Adaptive Control & Reinforcement Learning (MRAC-RL) approach to developing online policies for systems in which modeling errors occur…

cs.LG20215 cited

A High-order Tuner for Accelerated Learning and Control

Spencer McDonald, Yingnan Cui, Joseph E. Gaudio +1

Gradient-descent based iterative algorithms pervade a variety of problems in estimation, prediction, learning, control, and optimization. Recently iterative algorithms based on hig…