Stochastic adaptive one-step-ahead optimal controllers based on input matching

Author

Lo, Kueiming ; Zhang, Dachun

Author_Institution

Dept. of Math. Sci., Tsinghua Univ., Beijing, China

Volume

45

Issue

5

fYear

2000

fDate

5/1/2000 12:00:00 AM

Firstpage

980

Lastpage

983

Abstract

Optimal adaptive controller based on the ELS algorithm is established using the input matching technique. The control signal is reduced to a constant weighted sum of the measurable information-state vector components using a one-step-ahead quadratic cost function to govern the behavior of the stochastic linear systems. The control effort can be estimated globally. The algorithm also predicts the convergence rate. With no excitation condition, the closed-loop system is globally stable and the input converges to the one-step-ahead optimal input

Keywords

adaptive control; closed loop systems; convergence; least squares approximations; optimal control; stability; stochastic systems; ELS algorithm; LS algorithm; closed-loop system; convergence rate; global stability; input matching; least squares algorithm; measurable information-state vector components sum; one-step-ahead quadratic cost function; stochastic adaptive one-step-ahead optimal controllers; stochastic linear systems; Adaptive control; Control systems; Cost function; Impedance matching; Linear systems; Optimal control; Programmable control; Stochastic processes; Stochastic systems; Vectors;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/9.855567

Filename

855567