Adaptive control of continuous time linear stochastic system with quadratic cost functional

@article{AdamCzornik1996,
abstract = {An adaptive control problem for linear, continuous time stochastic system is described and solved in this paper. The unknown parameters in the model appear affinely in the drift term of the stochastic differential equation. The parameter estimates given by the maximum likelihood method are used to define the feedback gain. It is proved that the parameter estimates are strongly consistent and the cost functional reaches its minimum, i.e. the adaptive control is optimal. In this paper the continuity of the solution of the algebraic Riccati equation as a function of coefficient is also verified. The continuity is important for applications to problems in adaptive control.},
author = {Adam Czornik},
journal = {Mathematica Applicanda},
keywords = {Stochastic learning and adaptive control; Adaptive control},
language = {eng},
number = {39},
pages = {null},
title = {Adaptive control of continuous time linear stochastic system with quadratic cost functional},
url = {http://eudml.org/doc/293306},
volume = {25},
year = {1996},
}

TY - JOUR
AU - Adam Czornik
TI - Adaptive control of continuous time linear stochastic system with quadratic cost functional
JO - Mathematica Applicanda
PY - 1996
VL - 25
IS - 39
SP - null
AB - An adaptive control problem for linear, continuous time stochastic system is described and solved in this paper. The unknown parameters in the model appear affinely in the drift term of the stochastic differential equation. The parameter estimates given by the maximum likelihood method are used to define the feedback gain. It is proved that the parameter estimates are strongly consistent and the cost functional reaches its minimum, i.e. the adaptive control is optimal. In this paper the continuity of the solution of the algebraic Riccati equation as a function of coefficient is also verified. The continuity is important for applications to problems in adaptive control.
LA - eng
KW - Stochastic learning and adaptive control; Adaptive control
UR - http://eudml.org/doc/293306
ER -