In this paper we present a method for using rational expectations in a stochastic linear-quadratic optimization framework in which the unknown parameters are updated through a learning scheme. We use the QZ decomposition as suggested by Sims (1996) to solve the rational expectations part of the model. The parameter updating is done with the Kalman filter and the optimal control is calculated us...

A challenging topic in the field of planetary rover simulations is the modeling of the contact between the rover and its environment. Multibody simulation models are used to represent the kinematic structure of a wheeled rover, but its interface with the environment relies on sand-wheel contact dynamics. A new advanced contact model is presented and tuned according to single wheel experiments b...

In this paper, following a two-stage methodology, the differential quadrature element (DQE) model of a three-story frame structure is updated for the vibration analysis. In the first stage, the mass and stiffness matrices are updated using the experimental natural frequencies. Then, having the updated mass and stiffness matrices, the structural damping matrix is updated to minimize the error be...

in this study, a new stochastic model is proposed to deal with a multi-product, multi-period, multi-stage, multi-site production and transportation supply chain planning problem under demand uncertainty. a two-stage stochastic linear programming approach is used to maximize the expected profit. decisions such as the production amount, the inventory level of finished and semi-finished product, t...

In this paper, a stochastic two-stage model is offered for optimization of the day-ahead scheduling of the microgrid. System uncertainties including dispatchable distributed generation and energy storage contingencies are considered in the stochastic model. For handling uncertainties, Monte Carlo simulation is employed for generation several scenarios and then a reduction method is used to decr...

Stochastic differential equations (SDEs) have been applied by engineers and economists because it can express the behavior of stochastic processes in compact expressions. In this paper, by using Grunwald-Letnikov fractional derivative, the stochastic differential model is improved. Two numerical examples are presented to show efficiency of the proposed model. A numerical optimization approach b...

A novel state-space model of a multi-node supply chain is presented, controlled via local proportional inventory-replenishment policies. The model is driven by a stochastic sequence representing customer demand. The model is analyzed under stationarity conditions and a simple recursive scheme is developed for updating its covariance matrix. This allows us to characterize the “bullwhip effect” (...

In this paper a novel algorithm for estimating the parametric form of the camera motion is proposed. A novel stochastic vector field model is presented which can handle smooth motion patterns derived from long periods of stable camera movement and also can cope with rapid motion changes and periods where camera remains still. A set of rules for robust and online updating of the model parameters...