DocumentCode :
3255922
Title :
Stochastic online sensor scheduler for remote state estimation
Author :
Junfeng Wu ; Yilin Mo ; Ling Shi
Author_Institution :
Dept. of Electron. & Comput. Eng., Hong Kong Univ. of Sci. & Technol., Kowloon, China
fYear :
2013
fDate :
19-20 Aug. 2013
Firstpage :
84
Lastpage :
89
Abstract :
In this paper, a remote state estimation problem where a sensor measures the state of a linear discrete-time process in an infinite time horizon is considered. We aim to minimize the average estimation error subject to a limited sensor-estimator communication rate. We propose a stochastic online sensor schedule: whether or not the sensor sends data is based on its measurements and a stochastic holding time between the present and the most recent sensor-estimator communication instance. This decision process is formulated as a generalized geometric programming (GGP) optimization problem. It can be solved with a tractable computational complexity and provides a better performance compared with the optimal offline schedule. Numerical example is provided to illustrate main results.
Keywords :
computational complexity; decision theory; discrete time systems; geometric programming; networked control systems; sensors; state estimation; stochastic systems; GGP optimization problem; average estimation error; remote state estimation problem; stochastic generalized geometric programming optimization problem; stochastic holding time; stochastic infinite time horizon; stochastic linear discrete-time process; stochastic online sensor scheduler; stochastic optimal offline scheduling; stochastic sensor measures; stochastic sensor-estimator communication instance; stochastic sensor-estimator communication rate; tractable computational complexity; Estimation error; Optimization; Random variables; Schedules; Time measurement; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cyber-Physical Systems, Networks, and Applications (CPSNA), 2013 IEEE 1st International Conference on
Conference_Location :
Taipei
Type :
conf
DOI :
10.1109/CPSNA.2013.6614251
Filename :
6614251
Link To Document :
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