Current control for a shunt hybrid active power filter using recursive integral PI

This paper presents a current control method for a shunt hybrid active power filter （HAPF） using recursive integral PI algorithm. The method improves the performance of the HAPF system by reducing the influence of detection accuracy, time delay of instruction current calculation and phase displacement of output filter. Fuzzy logic based set-point weighing algorithm is combined in the control scheme to enhance its robustness and anti-interference ability. The proposed algorithm is easy to implement for engineering applications and easy to compute. Experiment results have verified the validity of the proposed controller. Furthermore, the proposed recursive integral PI algorithm can also be applied in the control of periodic current as in AC drivers.

Contribution to Harmonic Depollution Control by the Use of Adaptive Hybrid Filter Type TLC: Case of Control by Modulated Hysteresis

In this article, we propose a topology of a TLC-HAPF power filter as a harmonic compensator for an optimization of the pollution control of electrical networks. This filter consists of an active part and a passive part in order to reduce or limit switching losses during current injection into networks thanks to its TLC module. This topology also provides solutions dynamic performance issues, resonance and lack of compensation capacity for imbalance cases. It also offers a greater range of compensation than conventional active models which do not offer as well as an intermediate circuit voltage in the order of 105 V to 109 V relatively lower than others models (600 v). A modulated hysteresis control of this topology is therefore also developed in this article and allows to obtain a network analysis on the three phases at three levels: source side, load side, and finally at the connection of the filter to the network, allowing to specify for these different positions the value of the current spectrum and its THD at this well-defined moment.

Design and Development of an Intelligent Energy Management System for a Smart Grid to Enhance the Power Quality

MigroGrid(MG)has emerged to resolve the growing demand for energy.But because of its inconsistent output,it can result in various power quality(PQ)issues.PQ is a problem that is becoming more and more important for the reliability of power systems that use renewable energy sources.Similarly,the employment of nonlinear loads will introduce harmonics into the system and,as a result,cause distortions in the current and voltage waveforms as well as low power quality issues in the supply system.Thus,this research focuses on power quality enhancement in the MG using hybrid shunt filters.However,the performance of the filter mainly depends upon the design,and stability of the controller.The efficiency of the proposed filter is enhanced by incorporating an enhanced adaptive fuzzy neural network(AFNN)controller.The performance of the proposed topology is examined in a MATLAB/Simulink environment,and experimental findings are provided to validate the effectiveness of this approach.Further,the results of the proposed controller are compared with Adaptive Fuzzy Back-Stepping(AFBS)and Adaptive Fuzzy Sliding(AFS)to prove its superiority over power quality improvement in MG.From the analysis,it can be observed that the proposed system reduces the total harmonic distortion by about 1.8%,which is less than the acceptable limit standard.

An enhanced PSO-DEFS based feature selection with biometric authentication for identi¯cation of diabetic retinopathy

Recently,automatic diagnosis of diabetic retinopathy(DR)from the retinal image is the most significant ressearch topic in the medical applications.Diabetic macular edema(DME)is the.major reason for the loss of vision in patients suffering fom DR.Early identification of the DR enables to prevent the vision loss and encourage diabetic control activities.Many techniques are.developed to diagnose the DR.The major drawbacks of the existing techniques are low accuracy and high time complexity.To owercome these issues,this paper propases an enhanced particle swarm optimization differential evolution feature selection(PSO DEFS)based feature selection approach with biometric aut hentication for the identification of DR.Initially,a hybrid median filter(HMF)is used for pre processing the input images.Then,the pre-processed images are embedded with each other by using least significant bit(LSB)for authentication purpose.Si-multaneously,the image features are extracted using convoluted local tetra pattern(CLTrP)and Tamura features.Feature selection is performed using PSO DEFS and PSO-gravitational search algorithm(PSO GSA)to reduce time complexity.Based on some performance metrics,the PSO-DEFS is chosen as a better choice for feature selection.The feature selection is performed based on the fitness value.A multi-relevance vector machine(M-RVM)is introduced to dlassify the 13 normal and 62 abnormal images among 75 images from 60 patients.Finally,the DR patients are further dassified by M-RVM.The experimental results exhibit that the proposed approach achieves better accuracy,sensitivity,and specificity than the exist ing techniques.

Hybrid Common-mode EMI Filter Design for Electric Vehicle Traction Inverters

A feedforward current-sense current-compensation(CSCC)active EMI filter(AEF)for the direct current-side common-mode(CM)electromagnetic interference(EMI)suppression of high-power electric vehicle traction inverters is analyzed and designed.A detailed design of the components with formulas is provided based on an analysis of the CSCC AEF,including the CSCC AEF topology and its implementation.The feedforward active filter stage was implemented using a simple current transformer and a small circuit board.Only a small passive filter with a high resonant frequency is required for high-frequency noise attenuation.The filter’s effectiveness was validated using the simulation results and experimental measurements.

Hybrid Optical Comb Filter with Multi-Port Fiber Coupler for DWDM Optical Network

Optical comb filters based on multi-port fused fiber couplers are proposed and numerically analyzed, 3-arm MZI composed by 1×7 fiber splitter and 3×3 fiber coupler, and 2-stage cascaded FIR type MZI interleave filter.

Gain Flattening Filter for Hybrid Sb-Doped EDFA Using All-Fiber Mach-Zehnder Interferometers

We demonstrate a novel gain-flattening filter based on all fiber Mach-Zehnder interferometers for Sb-doped silica hybrid EDFA. A gain flatness of better than 0.9dB has been achieved for three concatenated filters in C-band.