The accuracy of the Kalman filter in state estimation depends on the knowledge of the
process and measurement noise covariances. These are usually treated as tuning …

State‐space models require an accurate knowledge of the process error (QQ) and
measurement error (RR) covariance matrices for exact state estimation. Even though the …

This paper is the second part of a two-part research work intended at realizing a systematic
computational and experimental analysis of the principal data-driven identification …

This paper aims at achieving real-time optimal speed estimation for an induction motor using
the Extended Kalman filter (EKF). Speed estimation is essential for fault diagnosis in Motor …

交直流混合输电技术的迅猛发展和电力电子设备在电力系统中普遍使用, 使电力系统电磁暂态
仿真分析及研究的必要性越来越高. 但是, 对实际大电力系统进行整体的电磁暂态仿真建模复杂 …

A novel model-based approach to design a full-order state observer for estimating the states
of a three-tank process has been attempted in this research study. State estimation has been …

The optimality of the Kalman filter for state-estimation depends on the knowledge of the
process and measurement noise covariance. In applications, these covariances are often …

This study introduces an adaptive relative navigation filter, employing correlation methods to
autonomously discern and estimate the impacts of unmodeled perturbations on a two …

The problem of adaptive Kalman filtering for a discrete observable linear time-varying
system with unknown noise covariance matrices is addressed in this paper. The …

The tire friction potential is the quantity characterizing the amount of friction remaining before
the tire begins to skid on the road. Knowing this quantity during a travel turns out to be …