2 citations · 2 across the 9 of their papers we have counts for
15 papers
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…
Motion Planning for Autonomous Vehicles: When Model Predictive Control Meets Ensemble Kalman Smoothing
Iman Askari, Yebin Wang, Vedeng M. Deshpande +1
Safe and efficient motion planning is of fundamental importance for autonomous vehicles. This paper investigates motion planning based on nonlinear model predictive control (NMPC)…
Meta-Learning for Physically-Constrained Neural System Identification
Ankush Chakrabarty, Gordon Wichern, Vedang M. Deshpande +3
We present a gradient-based meta-learning framework for rapid adaptation of neural state-space models (NSSMs) for black-box system identification. When applicable, we also incorpor…
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…
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…