A dual Kalman filter approach for state estimation via output-only acceleration measurements
A dual implementation of the Kalman filter is proposed for estimating the unknown input and
states of a linear state-space model by using sparse noisy acceleration measurements. The …
states of a linear state-space model by using sparse noisy acceleration measurements. The …
A novel unscented Kalman filter for recursive state-input-system identification of nonlinear systems
The unscented Kalman filter (UKF) has proven to be an effective approach for the
identification of nonlinear systems from limited output measurements. However, the …
identification of nonlinear systems from limited output measurements. However, the …
Outlier-resistant recursive filtering for multisensor multirate networked systems under weighted try-once-discard protocol
In this article, a new outlier-resistant recursive filtering problem (RF) is studied for a class of
multisensor multirate networked systems under the weighted try-once-discard (WTOD) …
multisensor multirate networked systems under the weighted try-once-discard (WTOD) …
Outlier-resistant sequential filtering fusion for cyber-physical systems with quantized measurements under denial-of-service attacks
In this paper, an outlier-resistant sequential fusion problem is concerned for cyber-physical
systems with quantized measurements under denial-of-service attacks. The multi-sensor …
systems with quantized measurements under denial-of-service attacks. The multi-sensor …
Performance analysis of the generalised projection identification for time‐varying systems
F Ding, L Xu, Q Zhu - IET Control Theory & Applications, 2016 - Wiley Online Library
The least mean square methods include two typical parameter estimation algorithms, which
are the projection algorithm and the stochastic gradient algorithm, the former is sensitive to …
are the projection algorithm and the stochastic gradient algorithm, the former is sensitive to …
Real‐time system identification: an algorithm for simultaneous model class selection and parametric identification
In this article, a novel Bayesian real‐time system identification algorithm using response
measurement is proposed for dynamical systems. In contrast to most existing structural …
measurement is proposed for dynamical systems. In contrast to most existing structural …
Robust Gaussian Kalman filter with outlier detection
We consider the nonlinear robust filtering problem where the measurements are partially
disturbed by outliers. A new robust Kalman filter based on a detect-and-reject idea is …
disturbed by outliers. A new robust Kalman filter based on a detect-and-reject idea is …
Secure distributed dynamic state estimation in wide-area smart grids
Smart grid is a large complex network with a myriad of vulnerabilities, usually operated in
adversarial settings and regulated based on estimated system states. In this study, we …
adversarial settings and regulated based on estimated system states. In this study, we …
Detecting anomalies and de-noising monitoring data from sensors: A smart data approach
When monitoring safety levels in deep pit foundations using sensors, anomalies (eg, highly
correlated variables) and noise (eg, high dimensionality) exist in the extracted time series …
correlated variables) and noise (eg, high dimensionality) exist in the extracted time series …
Proportional–integral observer design for uncertain time-delay systems subject to deception attacks: An outlier-resistant approach
This article deals with the proportional–integral observer (PIO) design problem for a class of
linear systems with distributed time delays and randomly occurring parameter uncertainties …
linear systems with distributed time delays and randomly occurring parameter uncertainties …