Journal ArticleDOI
Kalman filtering approach to multi-rate information fusion in the presence of irregular sampling rate and variable measurement delay ☆
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TLDR
In this article, two Kalman filters are used to estimate the states based on each type of measurement and the estimates are fused in the next step by considering the correlation between them.About:
This article is published in Journal of Process Control.The article was published on 2017-05-01. It has received 68 citations till now. The article focuses on the topics: Extended Kalman filter & Fast Kalman filter.read more
Citations
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Journal ArticleDOI
A Review on Soft Sensors for Monitoring, Control, and Optimization of Industrial Processes
TL;DR: This work aims to present a comprehensive review of the developments since the start of the millennium of soft sensing, from the perspective of systems and control.
Journal ArticleDOI
Review and big data perspectives on robust data mining approaches for industrial process modeling with outliers and missing data
TL;DR: A systematic review of various state-of-the-art data preprocessing tricks as well as robust principal component analysis methods for process understanding and monitoring applications and big data perspectives on potential challenges and opportunities have been highlighted.
Journal ArticleDOI
A novel distributed extended Kalman filter for aircraft engine gas-path health estimation with sensor fusion uncertainty
TL;DR: A novel EKF algorithm for state estimation in the distributed framework with sensor fusion uncertainty is proposed, and it achieves better trade-off between the estimation accuracy and computational efforts.
Journal ArticleDOI
Quo vadis artificial intelligence?
TL;DR: In this paper , the authors discuss from a historical perspective how challenges were faced on the path of revolution of both the AI tools and the AI systems, in addition to the technical development of AI in the short to midterm, thoughts and insights are also presented regarding the symbiotic relationship of AI and humans in the long run.
References
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Journal ArticleDOI
Kalman filtering with intermittent observations
Bruno Sinopoli,Luca Schenato,Massimo Franceschetti,Kameshwar Poolla,Michael I. Jordan,S. Shankar Sastry +5 more
TL;DR: This work addresses the problem of performing Kalman filtering with intermittent observations by showing the existence of a critical value for the arrival rate of the observations, beyond which a transition to an unbounded state error covariance occurs.
Book
Kalman Filtering: Theory and Practice Using MATLAB
TL;DR: Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering and appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.
Journal ArticleDOI
Multisensor data fusion: A review of the state-of-the-art
TL;DR: A comprehensive review of the data fusion state of the art is proposed, exploring its conceptualizations, benefits, and challenging aspects, as well as existing methodologies.
Journal ArticleDOI
The Effect of the Common Process Noise on the Two-Sensor Fused-Track Covariance
Yaakov Bar-Shalom,Leon Campo +1 more
TL;DR: In this paper, the effect of the common process noise on the fusion of the state estimates of a target based on measurements obtained by two different sensors is examined in a multisensor environment where each sensor has its information processing (tracking) subsystem.
Journal ArticleDOI
Optimal Estimation in Networked Control Systems Subject to Random Delay and Packet Drop
TL;DR: It is shown that the minimum error covariance estimator is time-varying, stochastic, and it does not converge to a steady state, and the architecture is independent of the communication protocol and can be implemented using a finite memory buffer if the delivered packets have a finite maximum delay.
Related Papers (5)
Development of soft sensor by incorporating the delayed infrequent and irregular measurements
Yafeng Guo,Yu Zhao,Biao Huang +2 more