Inverse simulation is a technique whereby the control actions required for a modelled vehicle to fly a specified manoeuvre can be established. In this paper the general concepts of inverse simulation are introduced, and an algorithm designed specifically to achieve inverse simulation of a single main and tail rotor helicopter is presented. An important element of an inverse simulation is the de...

Inverse sampling design is generally considered to be appropriate technique when the population is divided into two subpopulations, one of which contains only few units. In this paper, we derive the Horvitz-Thompson estimator for the population mean under inverse sampling designs, where subpopulation sizes are known. We then introduce an alternative unbiased estimator, corresponding to post-st...

in this study, hydrus2d/3d software was used to estimate the hydraulic parameters of van genuchten-mualem model via inverse modeling using double-ring infiltrometers data in 3 different soil textures. nine scenarios of inverse modeling (divided in three groups) were considered with different number (5, 4 and 3) of fitted hydraulic parameters for optimization. in the first group, simulation was ...

This paper gives a global dynamic analysis of a two wheeled riding simulator that we have built and instrumented for the study of drivers behavior. These studies concern drive situations in normal urban scenario as well as dangerous driving situations such as skidding. The justification of the choice of the platform movements for a good feeling is discussed. Different models for inverse kinemat...

We present a new framework for prioritized multi-task motion/force control of fully-actuated robots. This work is established on a careful review and comparison of the state of the art. Some control frameworks are not optimal, that is they do not find the optimal solution for the secondary tasks. Other frameworks are optimal, but they tackle the control problem at kinematic level, hence they ne...

We present a method for obtaining efficient probabilistic solutions to geostatistical and linear inverse problems in spherical geometry. Our Spherical Direct Sequential Simulation (SDSSIM) framework combines information from possibly noisy observations, that provide either point on the model or are related by averaging kernel, statistics derived a-priori information. It generates realizations m...