most citedModeling and Optimal Control of Hybrid UAVs with Wind Disturbance

4 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

eess.SY2020

Sparse Sensing and Optimal Precision: Robust Optimal Observer Design with Model Uncertainty

Vedang M. Deshpande, Raktim Bhattacharya

We present a framework which incorporates three aspects of the estimation problem, namely, sparse sensor configuration, optimal precision, and robustness in the presence of model u…

eess.SY2020

A Lagrangian Method for Constrained Dynamics in Tensegrity Systems with Compressible Bars

Shao-Chen Hsu, Vaishnav Tadiparthi, Raktim Bhattacharya

This paper presents a Lagrangian approach to simulating multibody dynamics in a tensegrity framework with an ability to tackle holonomic constraint violations in an energy-preservi…

eess.SY20204 cited

Modeling and Optimal Control of Hybrid UAVs with Wind Disturbance

Sunsoo Kim, Niladri Das, Raktim Bhattacharya

This paper addresses modeling and control of a six-degree-of-freedom unmanned aerial vehicle capable of vertical take-off and landing in the presence of wind disturbances. We desig…

math.NA2019

A unified framework to generate optimized compact finite difference schemes

Vedang M. Deshpande, Raktim Bhattacharya, Diego A. Donzis

A unified framework to derive optimized compact schemes for a uniform grid is presented. The optimal scheme coefficients are determined analytically by solving an optimization prob…

math.OC2019

Privacy and Utility Aware Data Sharing for Space Situational Awareness from Ensemble and Unscented Kalman Filtering Perspective

Niladri Das, Raktim Bhattacharya

In this paper, we present an optimization-based formulation for privacy-utility tradeoff in the Ensemble and Unscented Kalman filtering framework, with a focus on space situational…

math.DS2019

Surrogate Modeling of Dynamics From Sparse Data Using Maximum Entropy Basis Functions

Vedang M. Deshpande, Raktim Bhattacharya

In this paper we present a data driven approach for approximating dynamical systems. A dynamics is approximated using basis functions, which are derived from maximization of the in…