Periodic use of time-varying state feedbacks for the receding horizon control of bilinear systems

This paper provides a receding horizon control method for SISO bilinear systems in the presence input constraints. Periodically-invariant sets are derived for a bilinear system with respect to a series of time-varying state feedback gains. The dual-mode control strategy is adopted and the periodically-invariant sets are used as target invariant sets. The state feedback gains used to define the target invariant sets are also used to render degrees of freedom to steer the current state into the target set. The region of attraction for the proposed algorithm is enlarged significantly with an extension of the horizon of periodicity while the on-line. Recommended by Editorial Board member Young Soo Suh under the direction of Editor Jae Weon Choi. This project is conducted through the Practical Application Project of Advanced Microsystems Packaging Program of Seoul Technopark, funded by the Ministry of Knowledge Economy. Young Il Lee was born in Korea in 1963. He received his B.Sc., M.S. and Ph.D. in Control and Instrumentation from Seoul National University. He is currently a Professor of the Dept. of Control and Instrumentation, Seoul National University of Technology. He spent two years at Oxford University as a Visiting Research Fellow. Basil Kouvaritakis was born in Athens, Greece in 1948. He was awarded First-Class Honours in Electrical Engineering from the Manchester Institute of Science and Technology, where he also received his Master and Doctorate. He is currently a Professor in Engineering at the Department of Engineering Science and a Tutorial Fellow at St Edmund Hall, Oxford University. Mark Cannon was born in England in 1971. He received M.Eng. and D.Phil. degrees from Oxford University and S.M. from Massachusetts Institute of Technology. He is currently a University Lecturer in Engineering and Fellow of St. Peter’s College, Oxford University.     

Investigation of quasi-elliptic hairpin dual-mode filters under different perturbations

This article presents a dual-mode resonator developed from a hairpin resonator with a reactive perturbation tapped at the mid-point. The dual-mode resonance characteristics are investigated intensive under both inductive and capacitive perturbations. Using this resonator, a method of synthesising the filter is also developed to determine the circuit layout directly according to the specified filter characteristics. Moreover, to improve the filter's performance, cross-coupling technique to realise quasi-elliptic responses is also discussed for both types of perturbations. Finally, two quasi-elliptic dual-mode filters were designed, fabricated and measured to verify the proposed theory.     

Parallel Density-Based Spatial Clustering with Dual-Functional Memristive Crossbar Array

Analog and digital switching performances in a Ta/HfO₂/RuO₂ (THR) memristor are studied to implement a density-based spatial clustering of applications with noise (DBSCAN) algorithm in a low-power, parallel-computing memristor crossbar structure. In the analog mode THR memristor, more than 256 states can be stored through a fine-tuning process with a denoising scheme. The analog mode crossbar array facilitates Euclidean distance calculation between any points in the given graphic dataset. In the digital mode, the on/off ratio of more than three orders of magnitude between the binary states is achieved, providing functionality to cluster the data points with a reduced number of operations. The parallel computing capacity of the adopted crossbar decreases the time complexity of the original DBSCAN from O(n²) to O(n). Through array-level simulations, the effectiveness of hardware functionality is validated using representative synthetic datasets and single-cell RNA sequences datasets.     

基于双模式分解多通道输入的VSC-STATCOM逆变器故障诊断模型

针对传统电压源型静止同步补偿器中逆变器故障诊断存在的信号特征提取不充分,深度学习网络识别能力不足以及高噪声情况下识别率较低等问题,提出了一种基于双模式分解、多通道输入(MCI)、并行卷积神经网络(PCNN)、双向长短时记忆(BiLSTM)网络和自注意力(SA)机制组合的逆变器故障诊断方法。首先利用变分模态分解和时变滤波经验模态分解对逆变器输出的三相电流进行分解,降低原始信号复杂程度,实现不同模态分量间的规律互补;其次,利用MCI-PCNN-BiLSTM-SA组合模型对特征矩阵进行深层特征提取、学习和识别;最后,通过仿真进行验证,结果表明所提方法特征提取能力较强,在无噪声情况下平均识别率高达99.48%,在高噪声情况下平均识别率达95.59%。     

Markov跳变系统的滚动时域鲁棒双模控制

针对一类具有输入和状态联合约束的不确定离散时间Markov跳变系统,提出滚动时域鲁棒双模控制的方法.基于椭圆不变集的性质,在椭圆不变集以外使用滚动时域控制,驱动状态进入椭圆不变集.一旦状态进入椭圆不变集,改为使用线性状态反馈控制以保证状态始终位于椭圆不变集内,并使系统均方稳定.控制器的求解转化为以线性矩阵不等式形式给出的半正定规划问题.为改进半正定规划问题的可行性,将自由终端成本的上界作为椭圆不变集的边界,在优化成本的同时得到一组压缩椭圆集,相对于固定椭圆不变集降低了保守性.仿真实例验证了所提出方法的可行性和有效性.     

适应智能变电站就地化线路保护的双模高密度预制光缆研究

针对智能变电站即插即用就地化线路保护装置通信与其他设备交互时单模和多模即双模光信号在同一光接口传输的要求,设计了一种性能可靠、连接快速的双模(单模+多模)高密度预制光缆。该预制光缆能长期在恶劣气候、环境下使用,光纤连接器具有低连接损耗和高回波损耗的特点。该预制光缆解决了现有预制光缆光传输单一、性能不可靠等问题,提高了光连接的高效性和可靠性。通过对双模预制光缆的测试和验证,表明该预制光缆性能优异,达到了预期的目标。     

基于双模调频分解的低压配电网同期线损率预测模型

为了高精度评价电力系统运行方式合理性以及电力企业运营状况,研究基于双模调频分解的低压配电网同期线损率预测模型,利用高精度的线损率预测结果提升电网运营管理性能。采集低压配电网电能传输信号,通过双模调频分解方法利用双模调频基函数分解信号,去除无用信号;利用分层式节点识别策略在分解后的配电信号中划分低压配电网的负荷节点,获取各负荷节点的注入电流;利用支持向量机方法建立同期线损率预测模型,将所获取的注入电流输入到模型中,输出线损率预测优化结果。试验结果表明,该预测模型的预测结果与实际结果极为吻合,平均绝对误差和均方根误差均不超过0.09%,证明该模型可有效预测低压配电网同期线损率,预测精度高,可为智能配电网运营管理提供有效依据。     

基于HPLC双模通信的多方式一致性测试系统

国家电网公司正在研究基于HPLC的双模通信技术,可应用于载波通信盲点场景、无线通信盲点场景和双模融合通信场景,以提高接入网的通信带宽、速率和覆盖率以及泛在电力物联网各类新业务支撑能力等。协议一致性测试是确保各厂家所研发通信模块间互联互通的关键所在。为后期验证双模通信模块的协议一致性,设计了一种适用三种研发阶段的双模通信模块一致性测试系统,并详述了测试系统各模块的设计及实现方案。以宽带微功率中CCO的单网络组网测试用例对系统功能进行验证,测试结果表明该系统可全自动实现不同测试方式下对双模通信模块的一致性测试。     

干涉式电压互感器的有限元分析

设计一种新型的光纤电压互感器以满足电力工业发展对高压电压互感器的要求,成为国内外的研究热点,为此基于石英晶体的逆压电效应,研制了一种双模干涉式的电子电压互感器并给出其基本原理即利用两个低阶模的干涉原理改善电压互感器的性能,为消除外界干扰、提高系统的测量精度提供理论根据。利用有限元软件对该互感器传感头进行电场强度分析和研究的结果显示:在峰值电压作用下,互感器传感头无击穿现象,满足了工程的需要,为光学电压互感器的电压测量的稳定性提供了理论依据。该互感器信号的感应和传输都在光纤中进行,光路结构简单,抗干扰能力强,准确度高,安全可靠,是光学电压互感器设计的一种新思路。     

一种新型光纤电压互感器的设计

介绍了一种新型110 kV光纤电压互感器的基本原理和初步设计方案.该电压互感器基于石英晶体的逆压电效应,电压通过金属电极加在石英晶体的两端,电场方向和石英晶体纵向传感轴平行.利用2段椭圆芯双模光纤,第1段作为传感光纤缠绕在石英晶体上以感知交变电场导致的压电形变,第2段作为接收光纤跟踪Lp 01模式和LPeven 11模式之间相位差的变化.该方法源于白光干涉技术,包括2个级联的干涉仪,分别为传感干涉仪和接收干涉仪.采用780 nm,5 mW低相干多模激光二极管作为光源.讨论了互感器的参数设计,包括机械设计、双模光纤参数的研究以及传感光纤匝数的估算.最后介绍了互感器的工作条件和性能指标要求.