An extension of the LQR/LQG methodology to systems with saturating actuators, referred to as SLQR/SLQG, where S stands for saturating, is obtained. The development is based on the method of stochastic linearization, whereby the saturation is replaced by a xed gain, calculated as a function of the variance of the signal at its input. Using the stochastically linearized system and the Lagrange mu...

Abstract Lossless positive-real systems have been widely studied in the literature. They are which energy is entirely transferred between input and output. In this paper, new aspects related to linear quadratic gaussian (LQG) control of lossless reported including both continuous-time discrete-time cases. Direct formulas for calculation optimal gains will be introduced properties different stru...

Attempts to unify Gravity Theory and Quantum Field (QFT) under Loop (LQG), are diverse; a dividing line between classical quantum is sought with Schrödinger cat-state experiments. A Primordial Theory-based alternative presented, gravity-based harmonic oscillator developed. With theory applied at micro-scales gravity meso- macro-scales, this scale-gap contributes the conceptual problems associat...

The linear quadratic Gaussian (LQG) control for a quadrotor unmanned aerial vehicle (UAV) under false data injection attacks is studied. LQG depends on optimal state estimation, while this type of makes the estimation unimplementable in practice. To address problem, authors prose framework to detect and then augment information controller design. Based framework, designed sufficient condition s...

In this paper, we study the dynamics of k-essence in loop quantum cosmology (LQC). The indicates that gravity (LQG) effect plays a key role only early epoch universe and is diluted at later stage. fixed points LQC are basically consistent with standard Friedmann-Robertson-Walker (FRW) cosmology. For most attractor solutions, stability conditions agreement for FRW universe. But some special poin...

Optimal control theory and machine learning techniques are combined to formulate and solve in closed form an optimal control formulation of online learning from supervised examples with regularization of the updates. The connections with the classical linear quadratic gaussian (LQG) optimal control problem, of which the proposed learning paradigm is a nontrivial variation as it involves random ...

We introduce a generic solver for dynamic portfolio allocation problems when the market exhibits return predictability, price impact and partial observability. We assume that the price modeling can be encoded into a linear state-space and we demonstrate how the problem then falls into the LQG framework. We derive the optimal control policy and introduce analytical tools that preserve the intell...

We generalize a model recently proposed for Euclidean quantum gravity to the case of Lorentzian signature. The main features of the Euclidean model are preserved in the Lorentzian one. In particular, the boundary Hilbert space matches the one of SU(2) loop quantum gravity. As in the Euclidean case, the model can be obtained from the Lorentzian Barrett-Crane model from a flipping of the Poisson ...

It is shown that the LQG optimal controller is a continuous function of the plant. The result is proved for a class of plants which contains the class of strictly proper nite-dimensional plants. The topology employed is the one generated by convergence of the closed loop transfer functions in an induced L 1 sense. This topology is slightly stronger than the usual (H 2) gap metric convergence on...

This paper explores the application of numerical optimal control (NOC) to the synthesis of motion cueing algorithms for race-car simulators. These techniques are used to design washout filters that address the limitations of the commonly-employed linear quadratic Guassian (LQG) regulator and classical frequency shaping strategies. The primary disadvantage of the LQG and classical tuning methods...