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Direct field oriented control scheme for space vector modulated AC/DC/AC converter fed induction motor

F. BENCHABANE, A. TITAOUINE, O. BENNIS, K. YAHIA, D. TAIBI

《能源前沿（英文）》 2012年第6卷第2期页码 129-137 doi: 10.1007/s11708-012-0183-0

摘要： This paper investigates a Luenberger flux observer with speed adaptation for a direct field oriented control of an induction motor. An improved method of speed estimation that operates on the principle of speed adaptive flux and current observer has been proposed. An observer is basically an estimator that uses a plant model and a feedback loop with measured stator voltage and current. Simulation results show that the proposed direct field oriented control with the proposed observer provides good performance dynamic characteristics. The induction motor is fed by an indirect power electronics converter. This indirect converter is controlled by a sliding mode technique that enables minimization of harmonics introduced by the line converter, as well as the control of the power factor and DC-link voltage. The robustness of the overall system is studied using simulation for different operating modes and varied parameters.

关键词： induction motor direct filed oriented control Luenberger observer estimation space vector modulation (SVM) sliding mode control boost-rectifier

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Fault tolerant control strategy for modular PWM current source inverter

《能源前沿（英文）》 2023年第17卷第2期页码 228-238 doi: 10.1007/s11708-022-0852-6

摘要： In this paper, a fault-tolerant control method for an input-series output-parallel modular grid-tied pulse-width modulation (PWM) current source inverter is proposed to address the most commonly seen single symmetrical gate-commutated thyristor (SGCT) open-circuit fault problems. This method actively offsets the neutral point of the current space vector to ensure a sinusoidal output of the grid current, and it can achieve the upper limit power of the inverter under the condition of a single SGCT open-circuit fault. In addition, an active damping control method based on grid harmonic current feedback is proposed after analyzing the influence of the transformer ferromagnetic resonance caused by the neutral point offset on the power quality of the grid current. It has been demonstrated that the proposed method effectively suppresses the resonance caused by the transformer and the modified modulation, improving the grid current’s power quality.

关键词： current source converter (CSC) fault-tolerant control space vector modulation active damping resonance suppression power quality

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Robust SVM-direct torque control of induction motor based on sliding mode controller and sliding mode observer

Abdelkarim AMMAR,Amor BOUREK,Abdelhamid BENAKCHA

《能源前沿（英文）》 2020年第14卷第4期页码 836-849 doi: 10.1007/s11708-017-0444-z

摘要： This paper proposes a design of control and estimation strategy for induction motor based on the variable structure approach. It describes a coupling of sliding mode direct torque control (DTC) with sliding mode flux and speed observer. This algorithm uses direct torque control basics and the sliding mode approach. A robust electromagnetic torque and flux controllers are designed to overcome the conventional SVM-DTC drawbacks and to ensure fast response and full reference tracking with desired dynamic behavior and low ripple level. The sliding mode controller is used to generate reference voltages in stationary frame and give them to the controlled motor after modulation by a space vector modulation (SVM) inverter. The second aim of this paper is to design a sliding mode speed/flux observer which can improve the control performances by using a sensorless algorithm to get an accurate estimation, and consequently, increase the reliability of the system and decrease the cost of using sensors. The effectiveness of the whole composed control algorithm is investigated in different robustness tests with simulation using Matlab/Simulink and verified by real time experimental implementation based on dS pace 1104 board.

关键词： induction motor direct torque control (DTC) space vector modulation (SVM) sliding mode control (SMC) sliding mode observer (SMO) dS1104

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基于低复杂度最大似然的STBC-MIMO系统高效调制识别方法 Article

Maqsood H. SHAH, Xiao-yu DANG

《信息与电子工程前沿（英文）》 2020年第21卷第3期页码 465-475 doi: 10.1631/FITEE.1800306

摘要：针对正交空时块编码的多输入多输出系统（STBC-MIMO），提出一种基于低复杂度似然比的自动调制识别方法。使用迫零均衡技术修正平均似然比检验函数（ALRT）。与目前MIMO系统调制识别中使用的ALRT相比，本文提出的检验函数具有较低计算复杂度。在接收机具有非理想信道状态信息的条件下，对提出的方法在盲信道场景中进行分析。同时对不同天线数目的场景进行性能分析，利用Alamouti-STBC系统（2×2与2×1）和空时发射分集（4×4）的不同发射和接收天线配置验证本文所提方法，其中一些常用的调制方式被用作调制测试池。以正确识别率为指标，采用蒙特卡罗仿真法评价本文方法。仿真结果表明，该方法在低信噪比下有较好分类精度，在信道状态信息估计误差方差大的情况下有较好稳健性。

关键词：多输入多输出；空时块编码；最大似然；自动调制识别；迫零均衡

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基于双正交复序列的高效扩频调制方法

史小红

《中国工程科学》 2012年第14卷第3期页码 108-112

摘要：

提出了一种采用双正交复序列的高效扩频调制与解调方法（DoCS）。输入数据比特流被分割为长度为M的组，每组的M比特作为输入码字，从2M-2个长度为L的DoCS序列中选择一条序列进行发送，被选中的序列以QPSK方式调制在载波上，实现扩频通信。文中还提出了一种前向相位校正(FPC)方法来解决该系统中收发两端的载波同步问题。

关键词：调制与解调技术高效扩频调制前向相位校正双正交码

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A driving pulse edge modulation technique and its complex programming logic devices implementation

Xiao CHEN,Dong-chang QU,Yong GUO,Guo-zhu CHEN

《信息与电子工程前沿（英文）》 2015年第16卷第12期页码 1088-1098 doi: 10.1631/FITEE.1500111

摘要： With the continual increase in switching speed and rating of power semiconductors, the switching voltage spike becomes a serious problem. This paper describes a new technique of driving pulse edge modulation for insulated gate bipolar transistors (IGBTs). By modulating the density and width of the pulse trains, without regulating the hardware circuit, the slope of the gate driving voltage is controlled to change the switching speed. This technique is used in the driving circuit based on complex programmable logic devices (CPLDs), and the switching voltage spike of IGBTs can be restrained through software, which is easier and more flexible to adjust. Experimental results demonstrate the effectiveness and practicability of the proposed method.

关键词： Driving pulse edge modulation Switching voltage spike Complex programmable logic device (CPLD) Active gate drive

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基于核空间非线性特征提取的图像质量评价方法 Article

Yong DING,Nan LI,Yang ZHAO,Kai HUANG

《信息与电子工程前沿（英文）》 2016年第17卷第10期页码 1008-1017 doi: 10.1631/FITEE.1500439

摘要：概要：在实现对与人类视觉感知相一致的图像质量的客观评价中，如何提取图像的视觉感知特征至关重要。不同于传统方法中通过线性变换或模型表达图像的方式，本文采用高维空间的一种数学表达来揭示图像的统计特性，通过引入核独立分量分析（kernel independent component analysis, KICA）方法实现非线性转化和图像的高维特征提取。从而提出一种基于非线性特征提取的全参考图像质量评价方法。在LIVE、TID2008和CSIQ等图像质量评价数据库上的实验结果表明，图像的非线性特征更有利于图像内在质量的描述，并且本文提出的方法性能良好，与主观评价较为一致。

关键词：图像质量评价；全参考方法；特征提取；核空间；支持向量回归

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Cannabidiol prevents depressive-like behaviors through the modulation of neural stem cell differentiation

《医学前沿（英文）》 2022年第16卷第2期页码 227-239 doi: 10.1007/s11684-021-0896-8

摘要： Chronic stress impairs radial neural stem cell (rNSC) differentiation and adult hippocampal neurogenesis (AHN), whereas promoting AHN can increase stress resilience against depression. Therefore, investigating the mechanism of neural differentiation and AHN is of great importance for developing antidepressant drugs. The nonpsychoactive phytocannabinoid cannabidiol (CBD) has been shown to be effective against depression. However, whether CBD can modulate rNSC differentiation and hippocampal neurogenesis is unknown. Here, by using the chronic restraint stress (CRS) mouse model, we showed that hippocampal rNSCs mostly differentiated into astrocytes under stress conditions. Moreover, transcriptome analysis revealed that the FoxO signaling pathway was involved in the regulation of this process. The administration of CBD rescued depressive-like symptoms in CRS mice and prevented rNSCs overactivation and differentiation into astrocyte, which was partly mediated by the modulation of the FoxO signaling pathway. These results revealed a previously unknown neural mechanism for neural differentiation and AHN in depression and provided mechanistic insights into the antidepressive effects of CBD.

关键词： cannabidiol depression radial neural stem cells neurogenesis

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Liquefaction prediction using support vector machine model based on cone penetration data

Pijush SAMUI

《结构与土木工程前沿（英文）》 2013年第7卷第1期页码 72-82 doi: 10.1007/s11709-013-0185-y

摘要： A support vector machine (SVM) model has been developed for the prediction of liquefaction susceptibility as a classification problem, which is an imperative task in earthquake engineering. This paper examines the potential of SVM model in prediction of liquefaction using actual field cone penetration test (CPT) data from the 1999 Chi-Chi, Taiwan earthquake. The SVM, a novel learning machine based on statistical theory, uses structural risk minimization (SRM) induction principle to minimize the error. Using cone resistance ( ) and cyclic stress ratio ( ), model has been developed for prediction of liquefaction using SVM. Further an attempt has been made to simplify the model, requiring only two parameters ( and maximum horizontal acceleration ), for prediction of liquefaction. Further, developed SVM model has been applied to different case histories available globally and the results obtained confirm the capability of SVM model. For Chi-Chi earthquake, the model predicts with accuracy of 100%, and in the case of global data, SVM model predicts with accuracy of 89%. The effect of capacity factor ( ) on number of support vector and model accuracy has also been investigated. The study shows that SVM can be used as a practical tool for prediction of liquefaction potential, based on field CPT data.

关键词： earthquake cone penetration test liquefaction support vector machine (SVM) prediction

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A modified neural learning algorithm for online rotor resistance estimation in vector controlled induction

A. CHITRA,S. HIMAVATHI

《能源前沿（英文）》 2015年第9卷第1期页码 22-30 doi: 10.1007/s11708-014-0339-1

摘要： Online estimation of rotor resistance is essential for high performance vector controlled drives. In this paper, a novel modified neural algorithm has been identified for the online estimation of rotor resistance. Neural based estimators are now receiving active consideration as they have a number of advantages over conventional techniques. The training algorithm of the neural network determines its learning speed, stability, weight convergence, accuracy of estimation, speed of tracking and ease of implementation. In this paper, the neural estimator has been studied with conventional and proposed learning algorithms. The sensitivity of the rotor resistance change has been tested for a wide range of variation from -50% to+50% on the stability of the drive system with and without estimator. It is quiet appealing to settle with optimal estimation time and error for the viable realization. The study is conducted extensively for estimation and tracking. The proposed learning algorithm is found to exhibit good estimation and tracking capabilities. Besides, it reduces computational complexity and, hence, more feasible for practical digital implementation.

关键词： neural networks back propagation (BP) rotor resistance estimators vector control induction motor

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Unconfined compressive strength prediction of soils stabilized using artificial neural networks and support vector

Alireza TABARSA, Nima LATIFI, Abdolreza OSOULI, Younes BAGHERI

《结构与土木工程前沿（英文）》 2021年第15卷第2期页码 520-536 doi: 10.1007/s11709-021-0689-9

摘要： This study aims to improve the unconfined compressive strength of soils using additives as well as by predicting the strength behavior of stabilized soils using two artificial-intelligence-based models. The soils used in this study are stabilized using various combinations of cement, lime, and rice husk ash. To predict the results of unconfined compressive strength tests conducted on soils, a comprehensive laboratory dataset comprising 137 soil specimens treated with different combinations of cement, lime, and rice husk ash is used. Two artificial-intelligence-based models including artificial neural networks and support vector machines are used comparatively to predict the strength characteristics of soils treated with cement, lime, and rice husk ash under different conditions. The suggested models predicted the unconfined compressive strength of soils accurately and can be introduced as reliable predictive models in geotechnical engineering. This study demonstrates the better performance of support vector machines in predicting the strength of the investigated soils compared with artificial neural networks. The type of kernel function used in support vector machine models contributed positively to the performance of the proposed models. Moreover, based on sensitivity analysis results, it is discovered that cement and lime contents impose more prominent effects on the unconfined compressive strength values of the investigated soils compared with the other parameters.

关键词： unconfined compressive strength artificial neural network support vector machine predictive models regression

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Efficiency of scalar and vector intensity measures for seismic slope displacements

Gang WANG

《结构与土木工程前沿（英文）》 2012年第6卷第1期页码 44-52 doi: 10.1007/s11709-012-0138-x

摘要： Ground motion intensity measures are usually used to predict the earthquake-induced displacements in earth dams, soil slopes and soil structures. In this study, the efficiency of various single ground motion intensity measures (scalar ) or a combination of them (vector ) are investigated using the PEER-NGA strong motion database and an equivalent-linear sliding-mass model. Although no single intensity measure is efficient enough for all slope conditions, the spectral acceleration at 1.5 times of the initial slope period and Arias intensity of the input motion are found to be the most efficient scalar for flexible slopes and stiff slopes respectively. Vector can incorporate different characteristics of the ground motion and thus significantly improve the efficiency over a wide range of slope conditions. Among various vector considered, the spectral accelerations at multiple spectral periods achieve high efficiency for a wide range of slope conditions. This study provides useful guidance to the development of more efficient empirical prediction models as well as the ground motion selection criteria for time domain analysis of seismic slope displacements.

关键词： seismic slope displacements intensity measures empirical prediction

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Construction and identification of lentiviral RNA interference vector of rat leptin receptor gene

Zhengjuan LIU, Jie BIAN, Yuchuan WANG, Yongli ZHAO, Dong YAN, Xiaoxia WANG

《医学前沿（英文）》 2009年第3卷第1期页码 57-60 doi: 10.1007/s11684-009-0003-z

摘要： Leptin resistance is a main mechanism of acquired childhood obesity, and the suppression of long form of leptin receptor (OBRb) gene expression in diet-induced obese rats indicates that the down-regulation of OBRb gene expression plays a pivotal role in the mechanism of leptin resistance. The aim of the present study was to construct the lentiviral RNA interference (RNAi) vector of rat OBRb gene and evaluate the effects of siRNA on silencing OBRb gene expression. The target sequence of siRNA-OBRb was designed, and the complementary DNA containing both sense and antisense oligonucleotides was synthesized. After phosphorylation and annealing, these double-stranded DNA was cloned to pRNA-lentivector-VGFP to construct pRNA-Lenti-OBRb-VGFP recombinants with U6-containing promoter, target sequence and Poly III terminator. Then, the products were confirmed by electrophoresis and sequencing analysis, and the effects of RNAi on reducing gene expression were further confirmed by real-time polymerase chain reaction in transfected rat glioma cells expressing OBRb. The target sequence of siRNA-OBRb was successfully cloned to pRNA-lentivector-VGFP, and the RNAi protocol specifically reduced the expression of OBRb mRNA by approximately 80% compared with controls in transfected rat glioma cells. The successful construction of rat lentivirus vectors expressing OBRb-specific shRNA may be useful for further investigation .

关键词： receptors leptin RNA interference lentivirus vector

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The “Tiangong” Chinese Space Station project

Yang HONG

《工程管理前沿（英文）》 2018年第5卷第2期页码 278-283 doi: 10.15302/J-FEM-2018202

关键词： manned space station space station project basic design

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病理状态下肠道微生态的调节

王玉兰, 王保红, 吴俊芳, 江向洋, 唐惠儒, Ole H. Nielsen

《工程（英文）》 2017年第3卷第1期页码 83-89 doi: 10.1016/J.ENG.2017.01.013

摘要：

人类微生态是寄居在人体中的微生物聚集体，且主要存在于胃肠道(GIT) 中。肠道微生态随着人体发育而演化，并在人类健康和疾病中起着重要作用。近年来，由于微生态会影响宿主代谢、生理学和免疫系统发育，而且微生态紊乱可能导致许多疾病，其越来越受到人们的关注。肠道微生态可能与恶性肿瘤有一定联系，如胃癌和结直肠癌；也可能与其他一些疾病有关，如非酒精性脂肪肝(NAFLD)、被称为工业化世界“生活方式疾病”的肥胖和糖尿病、冠心病以及中枢神经系统紊乱。虽然分子技术革命为我们更准确地研究肠道微生态提供了必要的工具，但是我们需要更精确地阐明其与某些人类疾病病理变化的关系，明确微生态在不同疾病中的作用是新的治疗策略发展的基础。本文概述了肠道微生态对人类健康的重要影响以及调整肠道菌群结构的潜在用途，如菌群移植用于治疗耐药艰难梭菌(C. difficile) 的感染。通过微生态干预调整肠道区域以改善人类健康的概念虽刚刚兴起，但其治疗意义显著。因此，抑制有害菌、促进有益菌可能会保护人类健康，并且这些努力将为探索发展更加合理的治疗方案打下基础。

关键词：肠道菌群疾病菌群调节