DocumentCode
937773
Title
Final-value systems with Gaussian inputs
Author
Booton, Richard C., Jr.
Volume
2
Issue
3
fYear
1956
fDate
9/1/1956 12:00:00 AM
Firstpage
173
Lastpage
175
Abstract
A final-value system controls a response variable
over a time interval
with the objective of minimizing the difference between a desired value
and the final response value
. An ensemble of situations is considered, and the system input
and the desired response
are random variables that are statistically related. Physical limitations of the element being controlled result in a maximum value constraint on the system velocity
. Earlier results suggest that a system consisting of an estimator followed by a "bang-bang" servo is approximately optimum. The estimator uses the input to produce an estimate
of the desired response and the servo results in a system velocity as large in magnitude as possible and with the same sign as the difference
. The present paper shows that this system is the true optimum when the joint distribution of the input and the desired response is Gaussian and the error criterion is minimization of the average of a nondecreasing function of the magnitude of the error.
over a time interval
with the objective of minimizing the difference between a desired value
and the final response value
. An ensemble of situations is considered, and the system input
and the desired response
are random variables that are statistically related. Physical limitations of the element being controlled result in a maximum value constraint on the system velocity
. Earlier results suggest that a system consisting of an estimator followed by a "bang-bang" servo is approximately optimum. The estimator uses the input to produce an estimate
of the desired response and the servo results in a system velocity as large in magnitude as possible and with the same sign as the difference
. The present paper shows that this system is the true optimum when the joint distribution of the input and the desired response is Gaussian and the error criterion is minimization of the average of a nondecreasing function of the magnitude of the error.Keywords
Bang-bang control; Control systems; Gaussian processes; Control systems; Cost function; Density functional theory; Electric variables control; Laboratories; Nonlinear control systems; Probability density function; Random variables; Research and development; Servomechanisms;
fLanguage
English
Journal_Title
Information Theory, IRE Transactions on
Publisher
ieee
ISSN
0096-1000
Type
jour
DOI
10.1109/TIT.1956.1056800
Filename
1056800
Link To Document