Modular System of Cascaded Converters Based onModel Predictive Control

A modular system of cascaded converters based on model predictive control(MPC)is proposed to meet the application requirements ofmultiple voltage levels and electrical isolation in renewable energy generation systems.The system consists of a Buck/Boost+CLLLC cascaded converter as a submodule,which is combined in series and parallel on the input and output sides to achieve direct-current(DC)voltage transformation,bidirectional energy flow,and electrical isolation.The CLLLC converter operates in DC transformer mode in the submodule,while the Buck/Boost converter participates in voltage regulation.This article establishes a suitable mathematical model for the proposed system topology,and uses MPC to control the system based on this mathematical model.Module parameters are designed and calculated,and simulation is built in MATLAB/Simulink to complete the simulation comparison experiment between MPC and traditional proportional integral(PI)control.Finally,a physical experimental platform is built to complete the physical comparison experiment.The simulation and physical experimental results prove that the control accuracy and response speed ofMPC are better than traditional PI control strategy.

Skin Detection Method Based on Cascaded AdaBoost Classifier

Skin detection has been considered as the principal step in many machine vision systems,such as face detection and adult image filtering.Among all these techniques,skin color is the most welcome cue because of its robustness.However,traditional color-based approaches poorly perform on the classification of skin-like pixels.In this paper,we propose a new skin detection method based on the cascaded adaptive boosting(AdaBoost) classifier,which consists of minimum-risk based Bayesian classifier and models in different color spaces such as HSV(hue-saturation-value),YCgCb(brightness-green-blue) and YCgCr(brightness-green-red).In addition,we have constructed our own database that is larger and more suitable for training and testing on filtering adult images than the Compaq data set.Experimental results show that our method behaves better than the state-ofthe-art pixel-based skin detection techniques on processing images with skin-like background.