Neural network (NN) models often struggle to remain accurate when underlying systems drift from training conditions, necessitating costly and time-consuming model maintenance. Traditional approaches – ...
Electric vehicles (EVs) have emerged as a promising trend for future development. Serving as the core energy source for EVs, lithium-ion batteries offer advantages. Accurate SoC estimation is vital ...
This paper proposes a new econometric model for the estimation of optimal hedge ratios (HRs): the Kalman filter error-correction model (KF–ECM). This paper proposes a new econometric model for the ...
Integrating GAN-based machine learning with nonlinear Kalman filtering for enhanced state estimation
This study introduces a novel approach for enhancing state estimation in non-linear dynamic systems by integrating Generative Adversarial Networks (GANs) with the Unscented Kalman Filter (UKF). While ...
(A) 3D model of the manipulator structure, consisting of 3 continuum segments. The manipulator operates in the plane. (B) Close-up view of the revolute joint between adjacent disks. (C) Diagram ...
This article presents an aircraft jet engine sensor fault diagnostics and prediction implementation using a bank of Kalman filters and a Fast Fourier Transform Predictive analytics and fault ...
It appears that no particular approximate [nonlinear] filter is consistently better than any other, though . . . any nonlinear filter is better than a strictly linear one. 1 The Kalman filter is a ...
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