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eess.SY2024
Optimal State Estimation in the Presence of Non-Gaussian Uncertainty via Wasserstein Distance Minimization
Himanshu Prabhat, Raktim Bhattacharya
This paper presents a novel distribution-agnostic Wasserstein distance-based estimation framework. The goal is to determine an optimal map combining prior estimate with measurement…
eess.SY2024
A Convex Optimization Framework for Computing Robustness Margins of Kalman Filters
Himanshu Prabhat, Raktim Bhattacharya
This paper proposes a novel convex optimization framework for designing robust Kalman filters that guarantee a user-specified steady-state error while maximizing process and sensor…
eess.SY2024
Quantifying Maximum Actuator Degradation for a Given Performance with Full-State Feedback Control
Hrishav Das, Eliot Nychka, Raktim Bhattacharya
In this paper, we address the issue of quantifying maximum actuator degradation in linear time-invariant dynamical systems. We present a new unified framework for computing the sta…