1 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
Probe Sets for Nonlinear Kalman Filtering: Multi-Center Gains and Covariance Recalibration
Shida Jiang, Shengyu Tao, Scott Moura
Kalman filters (KFs) choose the gain as the product of the state-measurement cross-covariance and the inverse of the innovation covariance. In nonlinear systems, the predictive dis…
CAR-EnKF: A Covariance-Adaptive and Recalibrated Ensemble Kalman Filter Framework
Shida Jiang, Shengyu Tao, Zihe Liu +1
The ensemble Kalman filter (EnKF) is widely used for nonlinear and high-dimensional state estimation because it replaces explicit covariance propagation with ensemble statistics. H…
Model-Agnostic Energy Throughput Control for Range and Lifetime Extension of Electric Vehicles via Cell-Level Inverters
Shida Jiang, Shengyu Tao, Vincent Molina +2
A conventional electric vehicle (EV) powertrain relies on a centralized high-voltage DC-AC inverter, thereby limiting cell-level control and potentially reducing overall driving ra…
Design Guidelines for Nonlinear Kalman Filters via Covariance Compensation
Shida Jiang, Jaewoong Lee, Shengyu Tao +1
Nonlinear extensions of the Kalman filter (KF), such as the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), are indispensable for state estimation in complex dy…