Optimal Kalman Filtering for a Class of State Delay Systems with Randomly Multiple Sensor Delays
Joint Authors
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-24
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
The optimal Kalman filtering problem is investigated for a class of discrete state delay stochastic systems with randomly multiple sensor delays.
The phenomenon of measurement delay occurs in a random way and the delay rate for each sensor is described by a Bernoulli distributed random variable with known conditional probability.
Based on the innovative analysis approach and recursive projection formula, a new linear optimal filter is designed such that, for the state delay and randomly multiple sensor delays with different delay rates, the filtering error is minimized in the sense of mean square and the filter gain is designed by solving the recursive matrix equation.
Finally, a simulation example is given to illustrate the feasibility and effectiveness of the proposed filtering scheme.
American Psychological Association (APA)
Chen, Dongyan& Xu, Long. 2014. Optimal Kalman Filtering for a Class of State Delay Systems with Randomly Multiple Sensor Delays. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1033956
Modern Language Association (MLA)
Chen, Dongyan& Xu, Long. Optimal Kalman Filtering for a Class of State Delay Systems with Randomly Multiple Sensor Delays. Abstract and Applied Analysis No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-1033956
American Medical Association (AMA)
Chen, Dongyan& Xu, Long. Optimal Kalman Filtering for a Class of State Delay Systems with Randomly Multiple Sensor Delays. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1033956
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1033956