Open AccessKalman Filtering with Optimally Scheduled Measurements in Bandwidth Limited Communication Media
Author(s) -
Pasand Mohammad Mahdi Share,
Montazeri Mohsen
Publication year - 2017
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.17.0116.0566
Subject(s) - kalman filter , estimator , covariance , scheduling (production processes) , computer science , convex optimization , covariance intersection , mathematical optimization , norm (philosophy) , minification , real time computing , algorithm , control theory (sociology) , covariance matrix , regular polygon , estimation of covariance matrices , mathematics , control (management) , statistics , geometry , political science , law , artificial intelligence
A method is proposed for scheduling sensor accesses to the shared network in a networked control system. The proposed method determines the access order in which the sensors are granted medium access through minimization of the state estimation error covariance. Solving the problem by evaluating the error covariance for each possible ordered set of sensors is not practical for large systems. Therefore, a convex optimization problem is proposed, which yields approximate yet acceptable results. A state estimator is designed for the augmented system resulting from the incorporation of the optimally chosen communication sequence in the plant dynamics. A car suspension system simulation is conducted to test the proposed method. The results show promising improvement in the state estimation performance by reducing the estimation error norm compared to round‐robin scheduling.