Search results for "Forward"
showing 10 items of 280 documents
Analysis of thin high-k and silicide films by means of heavy ion time-of-flight forward-scattering spectrometry
2006
The use of forward scattered heavy incident ions in combination with a time-of-flight-energy telescope provides a powerful tool for the analysis of very thin (5–30 nm) films. This is because of greater stopping powers and better detector energy resolution for heavier ions than in conventional He-RBS. Because of the forward scattering angle, the sensitivity is greatly enhanced, thus reducing the ion beam induced desorption during the analysis of very thin films. The drawback of forward scattering angle is the limited mass separation for target elements. We demonstrate the performance of the technique with the analysis of 25 nm thick NiSi films and atomic layer deposited 6 nm thick HfxSiyOz f…
Crop density rather than ruderal plants explains the response of ancient segetal weeds
2018
AbstractThe influence of ruderal species and crop density on ancient segetal weeds was examined. The experiment was carried out on experimental plots with three different sewing densities of winter triticale. Weeding of ruderal taxa was applied on half of the plots to explore the relation between segetal and ruderal weeds. Variation in species composition by environmental variables was analysed by running Redundancy Analysis (RDA) combined with performing forward selection and variation partitioning for “weeding” and “crop density” as explanatory variables. Additionally, the effect of crop density and weeding was tested separately for segetal and ruderal species along the seasons with the u…
Adaptive Feedforward Control of a Pressure Compensated Differential Cylinder
2020
This paper presents the design, simulation and experimental verification of adaptive feedforward motion control for a hydraulic differential cylinder. The proposed solution is implemented on a hydraulic loader crane. Based on common adaptation methods, a typical electro-hydraulic motion control system has been extended with a novel adaptive feedforward controller that has two separate feedforward states, i.e, one for each direction of motion. Simulations show convergence of the feedforward states, as well as 23% reduction in root mean square (RMS) cylinder position error compared to a fixed gain feedforward controller. The experiments show an even more pronounced advantage of the proposed c…
Internal model-based feedback control design for inversion-free feedforward rate-dependent hysteresis compensation of piezoelectric cantilever actuat…
2018
Abstract This study proposes a new rate-dependent feedforward compensator for compensation of hysteresis nonlinearities in smart materials-based actuators without considering the analytical inverse model. The proposed rate-dependent compensator is constructed with the inverse multiplicative structure of the rate-dependent Prandtl–Ishlinskii (RDPI) model. The study also presents an investigation for the compensation error when the proposed compensator is applied in an open-loop feedforward manner. Then, an internal model-based feedback control design is applied with the proposed feedforward compensator to a piezoelectric cantilever actuator. The experimental results illustrate that the propo…
Anti-swing control of a hydraulic loader crane with a hanging load
2021
Abstract In this paper, anti-swing control for a hydraulic loader crane is presented. The difference between hydraulic and electric cranes are discussed to show the challenges associated with hydraulic actuation. The hanging load dynamics and relevant kinematics of the crane are derived to create the 2-DOF anti-swing controller. The anti-swing controller is added to the electro-hydraulic motion controller via feedforward. A dynamic simulation model of the crane is made, and the control system is evaluated in simulations with a path controller in actuator space. Simulation results show significant reduction in the load swing angle during motion. Experiments are carried out to verify the perf…
Performance Improvement of a Hydraulic Active/Passive Heave Compensation Winch Using Semi Secondary Motor Control: Experimental and Numerical Verific…
2020
In this paper, a newly developed controller for active heave compensated offshore cranes is compared with state-of-the-art control methods. The comparison is divided into a numerical part on stability margins as well as operational windows and an experimental validation of the expected performance improvement based on a full-scale testing on site with a crane rated to 250 metric tons. Such a crane represents the typical target for the new control method using a combination of active and passive hydraulic actuation on the main winch. The active hydraulic actuation is a hydrostatic transmission with variable-displacement pumps and variable-displacement motors. The new controller employs feedf…
Extreme Learning Machines for Data Classification Tuning by Improved Bat Algorithm
2018
Single hidden layer feed forward neural networks are widely used for various practical problems. However, the training process for determining synaptic weights of such neural networks can be computationally very expensive. In this paper we propose a new learning algorithm for learning the synaptic weights of the single hidden layer feedforward neural networks in order to reduce the learning time. We propose combining the upgraded bat algorithm with the extreme learning machine. The proposed approach reduces the number of evaluations needed to train a neural network and efficiently finds optimal input weights and the hidden biases. The proposed algorithm was tested on standard benchmark clas…
Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?
2020
Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…
Analyzing Cascading Effects in Interdependent Critical Infrastructures
2018
International audience; Critical Infrastructures (CIs) are resources that are essential for the performance of society, including its economy and its security. Large-scale disasters, whether natural or man-made, can have devastating primary (direct) effects on some CI and significant indirect effects (cascading effects) on other CIs, because CIs are interconnected and depend on each other’s services. Recent work by Laugé et al. expressed the dependency values among CIs as dependency matrices for various durations of the primary CI failure. For better preparedness and mitigation of CI failures knowledge of the weak points in CI interdependencies is crucial. To this effect, we have developed …
Exploring relationships between grid cell size and accuracy for debris-flow susceptibility models: a test in the Giampilieri catchment (Sicily, Italy)
2016
Debris flows are among the most hazardous phenomena in nature, requiring the preparation of suscep- tibility models in order to cope with this severe threat. The aim of this research was to verify whether a grid cell-based susceptibility model was capable of predicting the debris- flow initiation sites in the Giampilieri catchment (10 km2), which was hit by a storm on the 1st October 2009, resulting in more than one thousand landslides. This kind of event is to be considered as recurrent in the area as attested by historical data. Therefore, predictive models have been prepared by using forward stepwise binary logistic regression (BLR), a landslide inventory and a set of geo- environmental …