By Topic

Optimal measurement scheduling for state estimation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Shakeri, M. ; Dept. of Electr. & Syst. Eng., Connecticut Univ., Storrs, CT, USA ; Pattipati, K.R. ; Kleinman, D.L. ; Kalisetty, S.P.

The authors consider the problem of optimal allocation of measurement resources when: (1) the total measurement cost and time duration of measurements is fixed; and (2) the cost of an individual measurement varies inversely with the (controllable) measurement accuracy. The objective is to determine the time distribution of measurement variances that minimizes a measure of error in forecasting a discrete-time, vector stochastic process by a linear estimator. The metric of estimation error used is the trace of weighted sum of estimation error covariance matrices at various time indices. When the stochastic process is a scalar, it is shown that this problem reduces to solving a quadratic programming problem with nonnegativity constraints on the optimization variables. For the special case when the vector stochastic process is the state of a linear, finite-dimensional stochastic system, the problem reduces to the solution of a nonlinear optimal control problem

Published in:

Systems, Man and Cybernetics, 1992., IEEE International Conference on

Date of Conference:

18-21 Oct 1992