Papers by Keyword: Genetic Algorithm(GA)

Abstract: The description of hysteresis is one of the classical problems in magnetic materials. The progress in its solution determines the reliability of modeling and the quality of design of a wide range of contemporary devices, as well as devices that will be created in the future. The intensive investigations in hysteresis modeling were induced by the fact that accuracy models of magnetic hysteresis must be studied yet. In this paper, several identification procedures of the distribution functions of the Preisach model will be investigated by means of a genetic algorithm.The proposed approach has been applied to model the behavior of many samples and distribution functions are optimized which will give accurate results of the hysteresis loop. The results show the robustness and efficiency of genetic algorithm to model the phenomenon of hysteresis loop. This work can give solutions about the ferromagnetic material evaluations and shows the optimization of distribution functions according to the material behaviors.

Abstract: Visual Servoing to Moving Target with Fixed Hand-Eye Cameras Mounted at Hand of Robot is Inevitably Be Affected by Hand Dynamical Oscillations, then it is Hard to Keep Target at the Centre of Camera’s Image, since Nonlinear Dynamical Effects of Whole Manipulator Stand against Tracking Ability. in Order to Solve this Problem, an Eye-Vergence System, where the Visual Servoing Controller of Hand and Eye-Vergence is Controlled Independently, so that the Cameras can Observe the Target Object at the Center of the Camera Images through Eye-Vergence Functions. the Eyes with Light Mass Make the Cameras’ Eye-Sight Direction Rotate Quickly, so the Track Ability of the Eye-Vergence Motion is Superior to the One of Fixed Hand-Eye Configuration. in this Report Merits of Eye-Vengence Visual Servoing for Pose Tracking Have been Confirmed through Frequency Response Experiments.