46 citations · 137 across the 35 of their papers we have counts for
44 papers
Spectral Koopman Approach for Reconstructing State-space Geometry of Cislunar Restricted 3-Body Problem
Subhrajit Sinha, Sriram S. K. S. Narayanan, Raktim Bhattacharya +1
In this work, we propose a novel approach, based on the path integral formulation of Koopman spectrum, to discover the phase-space geometry of the planar Cislunar Restricted 3 Body…
On Improved Statistical Accuracy of Low-Order Polynomial Chaos Approximations
Vedang M. Deshpande, Raktim Bhattacharya
Polynomial chaos expansions provide surrogate models for stochastic systems, with coefficients typically derived using Galerkin projection, stochastic collocation, or least squares…
Optimal Control with Sparse Sensing and Actuation
Vedang M. Deshpande, Raktim Bhattacharya
In this paper, we present novel convex optimization formulations for designing full-state and output-feedback controllers with sparse actuation that achieve user-specified $\mathca…
Privacy-aware Gaussian Process Regression
Rui Tuo, Haoyuan Chen, Raktim Bhattacharya
We propose a novel theoretical and methodological framework for Gaussian process regression subject to privacy constraints. The proposed method can be used when a data owner is unw…
Optimal Sensor Precision for Multi-Rate Sensing for Bounded Estimation Error
Niladri Das, Raktim Bhattacharya
We address the problem of determining optimal sensor precisions for estimating the states of linear time-varying discrete-time stochastic dynamical systems, with guaranteed bounds…
Optimal Transport Based Refinement of Physics-Informed Neural Networks
Vaishnav Tadiparthi, Raktim Bhattacharya
In this paper, we propose a refinement strategy to the well-known Physics-Informed Neural Networks (PINNs) for solving partial differential equations (PDEs) based on the concept of…
Sensor Placement with Optimal Precision for Temperature Estimation of Battery Systems
Vedang M. Deshpande, Raktim Bhattacharya, Kamesh Subbarao
The temperature distribution in the battery significantly impacts the short-term and long-term performance of battery systems. Therefore, efficient, safe, and reliable battery syst…
Sensor Selection and Optimal Precision in Estimation Framework: Theory and Algorithms
Vedang M. Deshpande, Raktim Bhattacharya
We consider the problem of sensor selection for designing observer and filter for continuous linear time invariant systems such that the sensor precisions are minimized, and the es…
Sparse Sensing Architectures with Optimal Precision for Tracking Multi-agent Systems in Sensing-denied Environments
Vedang M. Deshpande, Raktim Bhattacharya
In this paper the tracking problem of multi-agent systems, in a particular scenario where a segment of agents entering a sensing-denied environment or behaving as non-cooperative t…
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…
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…
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…
Utility and Privacy in Object Tracking from Video Stream using Kalman Filter
Niladri Das, Raktim Bhattacharya
Tracking objects in Computer Vision is a hard problem. Privacy and utility concerns adds an extra layer of complexity over this problem. In this work we consider the problem of mai…
Computationally Efficient Attitude Estimation with Extended Filtering
Sunsoo Kim, Vaishnav Tadiparthi, Raktim Bhattacharya
Accurate state estimation using low-cost MEMS (Micro Electro- Mechanical Systems) sensors present on Commercial-off-the-shelf (COTS) drones is a challenging problem. Most UAV syste…
Data-driven Solution of Stochastic Differential Equations Using Maximum Entropy Basis Functions
Vedang M. Deshpande, Raktim Bhattacharya
In this paper we present a data-driven approach for uncertainty propagation. In particular, we consider stochastic differential equations with parametric uncertainty. Solution of t…
Robust LQR for Uncertain Discrete-Time Systems using Polynomial Chaos
Vaishnav Tadiparthi, Raktim Bhattacharya
In this paper, a polynomial chaos based framework for designing controllers for discrete time linear systems with probabilistic parameters is presented. Conditions for exponential-…
Nonlinear Attitude Estimation for Small UAVs with Low Power Microprocessors
Sunsoo Kim, Vaishnav Tadiparthi, Raktim Bhattacharya
Among algorithms used for sensor fusion for attitude estimation in unmanned aerial vehicles, the Extended Kalman Filter (EKF) is the most commonly used for estimation. In this pape…
H2 Optimized PID Control of Quad-Copter Platform with Wind Disturbance
Sunsoo Kim, Vedang Deshpande, Raktim Bhattacharya
Proportional-Integral-Derivative (PID) scheme is the most commonly used algorithm for designing the controllers for unmanned aerial vehicles (UAVs). However, tuning PID gains is a…
Optimal Transport Based Filtering with Nonlinear State Equality Constraints
Niladri Das, Raktim Bhattacharya
In this work we propose a framework to address the issue of state dependent nonlinear equality-constrained state estimation using Bayesian filtering. This framework is constructed…
Optimal Sensing Precision in Ensemble and Unscented Kalman Filtering
Niladri Das, Raktim Bhattacharya
We consider the problem of selecting an optimal set of sensor precisions to estimate the states of a non-linear dynamical system using an Ensemble Kalman filter and an Unscented Ka…
Kalman Filtering with Probabilistic Uncertainty in System Parameters
Sunsoo Kim, Vedang M. Deshpande, Raktim Bhattacharya
In this paper, we propose a robust Kalman filtering framework for systems with probabilistic uncertainty in system parameters. We consider two cases, namely discrete time systems,…
Sparse Sensing and Optimal Precision: An Integrated Framework for Optimal Observer Design
Vedang M. Deshpande, Raktim Bhattacharya
In this paper, we simultaneously determine the optimal sensor precision and the observer gain, which achieves the specified accuracy in the state estimates. Along with the unknown…
Eigen Value Analysis in Lower Bounding Uncertainty of Kalman Filter Estimates
Niladri Das, Raktim Bhattacharya
In this paper we are concerned with the error-covariance lower-bounding problem in Kalman filtering: a sensor releases a set of measurements to the data fusion/estimation center, w…
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…