Open AccessOn calculation of recursive M- and GM-estimates in LQG control systems
Author(s) -
Rimantas Pupeikis
Publication year - 2008
Publication title -
lietuvos matematikos rinkinys
Language(s) - English
Resource type - Journals
eISSN - 2335-898X
pISSN - 0132-2818
DOI - 10.15388/lmr.2008.18099
Subject(s) - linear quadratic gaussian control , control theory (sociology) , estimator , optimal projection equations , controller (irrigation) , parametric statistics , kalman filter , system identification , mathematics , lti system theory , linear system , computer science , noise (video) , optimal control , mathematical optimization , control (management) , statistics , data modeling , mathematical analysis , database , artificial intelligence , agronomy , image (mathematics) , biology
The aim of the given paper is development of a parametric identification approach for a closedloop system when the parameters of a discrete-time linear time-invariant (LTI) dynamic system as well as that of LQG (Linear Quadratic Gaussian) controller are not known and ought to be calculated. The recursive techniques based on an the maximum likelihood(M) and generalized maximum likelihood(GM) estimator algorithms are applied here in the calculation of the system as well as noise filter parameters. Afterwards, the recursive parameter estimates are used in each current iteration to determine unknown parameters of the LQG-controller, too. The results of numerical simulation by computer are discussed.