Bootstrap control

Author

Aronsson, M. ; Arvastson, L. ; Holst, J. ; Lindoff, B. ; Svensson, A.

Author_Institution

Centre for Math. Stat., Lund Inst. of Technol., Sweden

Volume

6

fYear

1999

fDate

1999

Firstpage

4516

Abstract

We present a method based on statistical bootstrap techniques to control linear stochastic systems. The optimal future control signal is derived in such a way that unknown noise distribution and uncertainties in parameter estimates are taken into account. This is achieved by resampling from existing data when calculating statistical distributions of future process values. The bootstrap algorithm takes care of arbitrary loss functions and unknown noise distribution even for small estimation sets. The efficient way of utilizing data implies that the method is also well suited for slowly time-varying stochastic systems

Keywords

linear systems; optimal control; parameter estimation; predictive control; statistical analysis; statistical process control; stochastic systems; uncertain systems; arbitrary loss functions; bootstrap control; linear stochastic systems; optimal future control signal; resampling; slowly time-varying stochastic systems; statistical bootstrap techniques; statistical distributions; uncertainties; unknown noise distribution; Communication system control; Control systems; Feedback loop; Open loop systems; Optimal control; Parameter estimation; Process control; Stochastic resonance; Stochastic systems; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 1999. Proceedings of the 1999

Conference_Location

San Diego, CA

ISSN

0743-1619

Print_ISBN

0-7803-4990-3

Type

conf

DOI

10.1109/ACC.1999.786441

Filename

786441