This paper introduces a new approach to reduce the computational load of nonlinear model based predictive controllers. The idea is based on dividing a long prediction horizon into only a few equidistant intervals with piecewise constant control signals. After solving a first dynamic optimization problem the prediction horizon is halved, keeping the second half of the solution fixed and doubling...

This paper addresses the design of a nonlinear time-invariant, dynamic state feedback receding horizon controller, which guarantees constraint satisfaction, robust stability and offset-free control of constrained, linear time-invariant systems in the presence of time-varying setpoints and unmeasured, persistent, additive disturbances. First, this objective is obtained by designing a dynamic, li...

It has previously been shown that the Einstein equation can be derived from the requirement that the Clausius relation dS=deltaQ/T hold for all local acceleration horizons through each spacetime point, where is one-quarter the horizon area change in Planck units and deltaQ and T are the energy flux across the horizon and the Unruh temperature seen by an accelerating observer just inside the hor...

This article provides importance sampling algorithms for computing the probabilities of various types ruin of spectrally negative Lévy risk processes, which are ruin over the infinite time horizon, ruin within a finite time horizon and ruin past a finite time horizon. For the special case of the compound Poisson process perturbed by diffusion, algorithms for computing probabilities of ruins by ...

In this article, we consider a receding horizon control of discrete-time state-dependent jump linear systems, particular kind of stochastic switching systems, subject to possibly unbounded random disturbances and probabilistic state constraints. Due to a nature of the dynamical system and the constraints, we consider a one-step receding horizon. Using inverse cumulative distribution function, w...

We approximate a Euclidean version of a D + 1 dimensional manifold with a bifurcate Killing horizon by a product of the two dimensional Rindler space R2 and a D − 1 dimensional Riemannian manifold M. We obtain approximate formulas for the Green functions. We study the behaviour of Green functions near the horizon and their dimensional reduction. We show that if M is compact then the massless mi...

this paper proposes a novel technique for solving generation scheduling and ramp rate constrained unit commitment. a modified objective function associated with a new start-up cost term is introduced in this paper. the proposed method is used to solve generating scheduling problem satisfying srr, minimum up and down time as well as ramp rate constraints. two case studies are conducted to implem...

A recent survey by Brookshire, et. al., (2006) suggests that forensic economists are mixed in their use of current versus historical data to estimate future net discount rates.1 Typically the choice is between a long-term average or simply the current prevailing rate.2 Cushing and Rosenbaum (2006) proposed an estimator that optimally uses the information in the past behavior of net discount rat...

The impact of the increase of greenhouse gases on Sahelian precipitation is very uncertain in both its spatial pattern and magnitude. In particular, the relative importance of internal variability versus external forcings depends on the time horizon considered in the climate projection. In this study we address the respective roles of the internal climate variability versus external forcings on...

This paper further explores the horizon effect in the optimal static and dynamic demand for risky assets under return predictability as documented by Barberis (2000). Contrary to the case of stocks, the optimal demand for long-term Government bonds of a buy-and-hold investor is not necessarily increasing in the investment horizon, and may in fact be decreasing for some initial levels of the pre...