DocumentCode :
2439299
Title :
Convergence and mean square stability of optimal estimators for systems with measurement packet dropping
Author :
Zhang, Huanshui ; Song, Xinmin ; Shi, Ling
Author_Institution :
Sch. of Control Sci. & Eng., Shandong Univ., Jinan, China
fYear :
2010
fDate :
7-10 Dec. 2010
Firstpage :
561
Lastpage :
566
Abstract :
This paper is concerned with estimation problem for discrete-time systems with packet dropping. A new optimal filter is derived by minimizing the mean squared estimation error. An optimal smoother is also derived in a similar way. Both estimators are designed by solving one deterministic Riccati equation. Both the convergence of the estimation error covariance and mean square stability of the estimator are proved under standard assumption. It is shown that the new estimator has smaller error covariance and has wider applications as compared with the MMSE estimator. One of the key techniques adopted in this paper is the introduction of the innovation sequence for the multiplicative noise systems.
Keywords :
Riccati equations; discrete time systems; mean square error methods; optimal control; stability; convergence; deterministic Riccati equation; discrete-time systems; estimation error covariance; mean square stability; mean squared estimation error; optimal filter; optimal smoother; packet dropping; Estimation; Kalman filters; Mathematical model; Riccati equations; Stability criteria; Discrete-time system; Riccati difference equation; convergence; mean square stability; optimal estimation; packet dropping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Automation Robotics & Vision (ICARCV), 2010 11th International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-7814-9
Type :
conf
DOI :
10.1109/ICARCV.2010.5707915
Filename :
5707915
Link To Document :
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