TY - JOUR

T1 - Optimal state estimation in networked systems via sensor control

AU - Matveev, Alexey S.

AU - Savkin, Andrey V.

PY - 2002/1/1

Y1 - 2002/1/1

N2 - We study a linear discrete-time partially observed system perturbed by white noises. The observations are transmitted to the controller via communication channels with irregular transmission times. Various measurement signals may incur independent delays, arrive at the estimator out of order, and be lost or corrupted. The estimator is given a dynamic control over the sensors data by selecting signals to be used from those arrived at the current time. The minimum variance state estimate and the optimal sensor control strategy are obtained. Ideas of model predictive control are employed to derive a non-optimal but implementable in real time method for sensor control.

AB - We study a linear discrete-time partially observed system perturbed by white noises. The observations are transmitted to the controller via communication channels with irregular transmission times. Various measurement signals may incur independent delays, arrive at the estimator out of order, and be lost or corrupted. The estimator is given a dynamic control over the sensors data by selecting signals to be used from those arrived at the current time. The minimum variance state estimate and the optimal sensor control strategy are obtained. Ideas of model predictive control are employed to derive a non-optimal but implementable in real time method for sensor control.

KW - Communication networks

KW - Optimal sensor control

KW - Optimal state estimation

UR - http://www.scopus.com/inward/record.url?scp=84945578473&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:84945578473

VL - 15

SP - 383

EP - 388

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

SN - 2405-8971

IS - 1

T2 - 15th World Congress of the International Federation of Automatic Control, 2002

Y2 - 21 July 2002 through 26 July 2002

ER -