Active probing for information in control systems with quantized state measurements: a minimum entropy approach

Author

Feng, Xiangbo ; Loparo, Kenneth A.

Author_Institution

Dept. of Syst. Eng., Case Western Reserve Univ., Cleveland, OH, USA

Volume

42

Issue

2

fYear

1997

fDate

2/1/1997 12:00:00 AM

Firstpage

216

Lastpage

238

Abstract

In this paper the effect of state quantization in scaler discrete-time linear control systems is studied by analyzing the system as a partially observed stochastic system. The problem of optimal state information gathering and filtering is investigated using information theoretic measures and formulating the state estimation problem as an entropy optimization problem. The active probing effect of the feedback control is thoroughly studied. Optimal feedback controls which minimize various types of entropy costs are determined, and it is shown that this problem is equivalent to an optimal control problem for a controlled Markov chain

Keywords

discrete time systems; feedback; information theory; linear systems; minimum entropy methods; optimal control; optimisation; state estimation; stochastic systems; Markov chain; active probing; discrete-time systems; feedback control; information theory; linear systems; minimum entropy; optimal control; optimization; state estimation; state quantization; stochastic system; Control systems; Cost function; Entropy; Feedback control; Information filtering; Information filters; Optimal control; Quantization; State estimation; Stochastic systems;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/9.554401

Filename

554401