In this paper, we study the existence of linear quadratic Gaussian (LQG)–balanced realizations for discrete-time infinite-dimensional systems. LQG-balanced realizations are those for which the smallest nonnegative self-adjoint solutions of the control and filter Riccati equations are equal. We show that the control (filter) Riccati equation has a nonnegative self-adjoint solution if and only if...

This paper presents an overview of some recent results concerning the emerging theory of minimax LQG control for uncertain systems with a relative entropy constraint uncertainty description. This is an important new robust control system design methodology providing minimax optimal performance in terms of a quadratic cost functional. The paper first considers some standard uncertainty descripti...

Using the dual Youla parametrizations of controller based coprime factor plant perturbations and plant based co-prime factor controller perturbations, we provide a computational procedure for computing an optimal innnite horizon Linear Quadratic Gaussian (LQG) controller from any stabilizing controller. The method allows us to calculate a new optimal LQG controller from a previous one when the ...

The strengthened discrete-time optimal projection equations (SDOPE) are presented in a form based on the delta operator. This form unifies discrete-time and continuous-time results. Based on this unification, recently established results and algorithms for finite and infinite-horizon fixed-order LQG compensation of discrete-time systems are carried over to the continuous-time case. The results ...

This paper applies the proportional-integral (PI) observer in connection with LQG and LQG/LTR design for discrete time systems. Both the prediction and the filtering versions of the PI observer are considered. We show that a PI observer makes it possible to obtain time recovery, i.e., exact recovery for t → ∞, under mild conditions. It is shown that LQG/LTR design is a special case of the cheap...

Design of power system stabilizer using Linear Quadratic Regulator (LQR) technique. Designs that ignore noise in a plant are likely to fail when implemented in actual conditions. Presence of the noise, which results in LQR output oscillating with very small magnitude. This type of unwanted noisy output is eliminated using Linear Quadratic Gaussian (LQG) Regulator. This paper presents techniques...

This article presents an “in-a-nutshell” yet self-contained introductory review on loop quantum gravity (LQG)—a background-independent, nonperturbative approach to a consistent quantum theory of gravity. Instead of rigorous and systematic derivations, it aims to provide a general picture of LQG, placing emphasis on the fundamental ideas and their significance. The canonical formulation of LQG, ...

BACKGROUND We investigated the applicability of linear quadratic Gaussian (LQG) methodology to the subcutaneous blood glucose regulation problem. We designed an LQG-based feedback control algorithm using linearization of a previously published metabolic model of type 1 diabetes. A key feature of the controller is a Kalman filter used to estimate metabolic states of the patient based on continuo...

This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for vectored thrust aerial vehicle (VTAV). With the SA strategy, we proposed a linear-quadratic-Gaussian (LQG) flight control procedure for an unmanned helicopter model with vectored thrust configuration. This LQG control for chosen model of VTAV has been verified by simulatio...

The Clowes & Campusano large quasar group (LQG) at z̄ = 1.28 has been re-examined using the quasar data from the DR7QSO catalogue of the Sloan Digital Sky Survey. In the 1991 discovery, the LQG impinged on the northern, southern and eastern limits of the survey. In the DR7QSO data, the western, northern and southern boundaries of the LQG remain essentially the same, but an extension eastwards of...