Case studies of optimum filter-controller design in sampled data systems
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Authors
McMichael, John Coleman
Skezas, George Christ
Subjects
Advisors
Strum, Robert D.
Date of Issue
1966-05
Date
Publisher
Monterey, California. U.S. Naval Postgraduate School
Language
en_US
Abstract
In this paper an investigation is made of the problem of estimating and
predicting the states of a linear, discrete, time-invariant, dynamic process
which is excited by Gaussian noise and where the observable states
are disturbed by Gaussian measurement noise. The concepts of optimum
filter design, originally developed by R. E. Kalman, are utilized. Also
we have closed the loop on two illustrative examples by determining the
optimal control for the plant as a function of the plant's state variables.
Here the concepts of a cost performance index and dynamic programming
(the latter originally developed by R. Bellman) are employed. The CDC 1604 digital computer, using Fortran 60 programming is utilized
in the solution of the optimum filter-controller design.
Type
Thesis
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Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.