activity
20182021
most citedAsynchronous Deep Model Reference Adaptive Control

27 citations · 27 across the 2 of their papers we have counts for

collaborators

6 papers

eess.SY2021

Stochastic Deep Model Reference Adaptive Control

Girish Joshi, Girish Chowdhary

In this paper, we present a Stochastic Deep Neural Network-based Model Reference Adaptive Control. Building on our work "Deep Model Reference Adaptive Control", we extend the contr…

cs.LG2021

Adaptive Policy Transfer in Reinforcement Learning

Girish Joshi, Girish Chowdhary

Efficient and robust policy transfer remains a key challenge for reinforcement learning to become viable for real-wold robotics. Policy transfer through warm initialization, imitat…

cs.RO202027 cited

Asynchronous Deep Model Reference Adaptive Control

Girish Joshi, Jasvir Virdi, Girish Chowdhary

In this paper, we present Asynchronous implementation of Deep Neural Network-based Model Reference Adaptive Control (DMRAC). We evaluate this new neuro-adaptive control architectur…

eess.SY2020

Robust and Precision Satellite Formation Flying Guidance Using Adaptive Optimal Control Techniques

Girish Joshi

The main focus of the work presented in this thesis is to develop an optimal control based formation flying control strategy for high precision formation flying of small satellites…

cs.LG2019

Deep Model Reference Adaptive Control

Girish Joshi, Girish Chowdhary

We present a new neuroadaptive architecture: Deep Neural Network based Model Reference Adaptive Control (DMRAC). Our architecture utilizes the power of deep neural network represen…

cs.AI2018

Cross-Domain Transfer in Reinforcement Learning using Target Apprentice

Girish Joshi, Girish Chowdhary

In this paper, we present a new approach to Transfer Learning (TL) in Reinforcement Learning (RL) for cross-domain tasks. Many of the available techniques approach the transfer arc…