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Multilevel Feature Moving Average Ratio Method for Fault Diagnosis of the Microgrid Inverter Switch

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IEEE/CAA Journal of Automatica Sinica 2017年第2期4卷 177-185页

作者： Zhanjun Huang ZhanShan Wang Huaguang Zhang College of Information Science and Engineering Northeastern University State Key Laboratory of Synthetical Automation for Process Industries IEEE

Multilevel feature moving average ratio method is proposed to realize an open-switch fault diagnosis for any switch of the microgrid inverter. The main steps of the proposed method include multilevel signal decomposition, coefficient reconstruction, absolute average ratio process and artificial neural network(ANN) classification. Specifically, multilevel signal decomposition is realized by using the means of multi resolution analysis to obtain the different frequency band coefficients of the three-phase current signal. The related coefficient reconstruction is executed to achieve signals decomposition in different levels. Furthermore,according to the obtained data, the absolute average ratio process is used to extract absolute moving average ratio of signal decomposition in different levels for the three-phase current.Finally, to intelligently classify the inverter switch fault and realize the adaptive ability, the ANN technology is applied.Compared to conventional fault diagnosis methods, the proposed method can accurately detect and locate the open-switch fault for any location of the microgrid inverter. Additionally, it need not set related threshold of algorithm and does not require normalization process, which is relatively easy to implement. The effectiveness of the proposed fault diagnosis method is demonstrated through detailed simulation results.

关键词： Absolute average ratio process fault diagnosis microgrid inverter multilevel feature moving average ratio neural network

Refined Jensen-Based Multiple Integral Inequality and Its Application to Stability of Time-Delay Systems

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IEEE/CAA Journal of Automatica Sinica 2018年第3期5卷 758-764页

作者： Jidong wang ZhanShan Wang Sanbo Ding Huaguang Zhang College of Information Science and Engineering Northeastern University Shenyang 110819 China State Key Laboratory of Synthetical Automation for Process Industries Shenyang 110819 China College of Electrical Engineering North China University of Water Resources and Electric Power Zhengzhou 450011 China IEEE

This paper investigates the stability of time-delay systems via a multiple integral approach. Based on the refined Jensen-based inequality, a novel multiple integral inequality is proposed. Applying the multiple integral inequality to estimate the derivative of Lyapunov-Krasovskii functional(LKF) with multiple integral terms, a novel stability condition is formulated for the linear time-delay systems. Two numerical examples are employed to demonstrate the improvements of our results.

关键词： Multiple integral approach refined Jensen-based multiple integral inequality(RJMII) stability analysis time-delay systems

Stochastic synchronization of neutral-type chaotic impulse neural networks with leakage delay and Markovian jumping parameters

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International Journal of Intelligent Computing and Cybernetics 2016年第3期9卷 237-254页

作者： Cheng-De Zheng ZhanShan Wang School of Science Dalian Jiaotong UniversityDalianPR China School of Information Science and Engineering Northeastern UniversityShenyangPR China

Purpose-The purpose of this paper is to develop a methodology for the stochastically asymptotic synchronization problem for a class of neutral-type chaotic neural networks with both leakage delay and Markovian jumping parameters under impulsive perturbations.Design/methodology/approach-The authors perform drive-response concept and time-delay feedback control techniques to investigate a class of neutral-type chaotic neural networks with both leakage delay and Markovian jumping parameters under impulsive perturbations.New sufficient criterion is established without strict conditions imposed on the activation functions.Findings-It turns out that the approach results in new sufficient criterion easy to be verified but without the usual assumption of the differentiability and monotonicity of the activation functions.Two examples show the effectiveness of the obtained results.Originality/value-The novelty of the proposed approach lies in removing the usual assumption of the differentiability and monotonicity of the activation functions,and the use of the Lyapunov functionalmethod,Jensen integral inequality,a novel Gu’s lemma,reciprocal convex and linear convex combination technique for the stochastically asymptotic synchronization problem for a class of neutral-type chaotic neural networks with both leakage delay and Markovian jumping parameters under impulsive perturbations.

关键词： Chaotic neural networks Jensen integral inequality Leakage delay Markovian jump Stochastically asymptotic synchronization Impulse

Consensus Robust Output Regulation of Discrete-time Linear Multi-agent Systems

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维普期刊数据库

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IEEE/CAA Journal of Automatica Sinica 2014年第2期1卷 204-209页

作者： Hongjing Liang Huaguang Zhang ZhanShan Wang Junyi wang School of Information Science and Engineering Northeastern University State Key Laboratory of Synthetical Automation for Process Industries (Northeastern University)

This paper deals with consensus robust output regulation of discrete-time linear multi-agent systems under a directed interaction topology. The digraph is assumed to contain a spanning tree. Every agent or subsystem is identical and uncertain, but subsystems have different external disturbances. Based on the internal model and general discrete-time algebraic Riccati equation, a distributed consensus protocol is proposed to solve the regulator problem. A numerical simulation demonstrates the effectiveness of the proposed theoretical results.

关键词： Multi-agent systems Robustness Eigenvalues and eigenfunctions Protocols Mathematical model Symmetric matrices Topology

A framework for investigating the air quality variation characteristics based on the monitoring data: Case study for Beijing during 2013–2016

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Journal of Environmental Sciences 2019年第7期31卷 225-237页

作者： Jixian Cui Jianlei Lang Tian Chen Shushuai Mao Shuiyuan Cheng ZhanShan Wang Nianliang Cheng Key Laboratory of Beijing on Regional Air Pollution Control College of Environmental & Energy Engineering Beijing University of Technology Beijing Municipal Environmental Monitoring Center

In this study, an analysis framework based on the regular monitoring data was proposed for investigating the annual/inter-annual air quality variation and the contributions from different factors(i.e., seasons, pollution periods and airflow directions), through a case study in Beijing from 2013 to 2016. The results showed that the annual mean concentrations(MC) of PM_(2.5), SO_2, NO_2 and CO had decreased with annual mean ratios of 7.5%, 28.6%, 4.6%and 15.5% from 2013 to 2016, respectively. Among seasons, the MC in winter contributed the largest fractions(25.8%～46.4%) to the annual MC, and the change of MC in summer contributed most to the inter-annual MC variation(IMCV) of PM_(2.5) and NO2. For different pollution periods, gradually increase of frequency of S-1(PM_(2.5), 0～ 75 μg/m^3) made S-1 become the largest contributor(28.8%) to the MC of PM_(2.5) in 2016, it had a negative contribution(-13.1%) to the IMCV of PM_(2.5); obvious decreases of frequencies of heavily polluted and severely polluted dominated(44.7% and 39.5%) the IMCV of PM_(2.5). For different airflow directions, the MC of pollutants under the south airflow had the most significant decrease(22.5%～62.5%), and those decrease contributed most to the IMCV of PM_(2.5)(143.3%),SO2(72.0%), NO_2(55.5%) and CO(190.3%); the west airflow had negative influences to the IMCV of PM_(2.5), NO_2 and CO. The framework is helpful for further analysis and utilization of the large amounts of monitoring data; and the analysis results can provide scientific supports for the formulation or adjustment of further air pollution mitigation policy.

关键词： Monitoring data analysis Air quality variations Airflow directions Pollution periods Beijing

Stability analysis of time-delay systems via parameter-dependent free-matrix-based double integral inequality

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Stability analysis of time-delay systems via parameter-depen...

Adaptive synchronization of different kinds of chaotic neural networks

第40届中国控制会议

作者： Yufeng Tian ZhanShan Wang College of Information Science and Engineering Northeastern University

Based on the free-matrix-based inequality methods, a parameter-dependent free-matrix-based double integral inequality is proposed in this paper, which includes the Wirtinger-based double integral inequality and free-matrix-based double integral inequality as its special cases. By introducing some free parameters and matrices into the inequality, more freedom can be provided in bounding the quadratic double integral. Furthermore, to investigate the effectiveness of the proposed inequality, a new delay dependent stability criterion is derived in terms of linear matrix inequalities. Numerical examples are given to demonstrate the advantages of the proposed method.

关键词： Linear system stability analysis parameter-dependent free-matrix-based double integral inequality time delay

来源： cnki会议评论

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cnki会议

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控制理论与应用（英文版） 2008年第2期6卷 201-207页

作者： Huanxin GUAN ZhanShan Wang Huaguang ZHANG School of Information Science and Engineering Northeastern University Shenyang Liaoning 110004 China Department of Continuous Education Shenyang InstitUte of Engineering Shenyang Liaoning 110034 China

The purpose of the paper is to present an adaptive control method for the synchronization of different classes of chaotic neural networks. A new sufficient condition for the global synchronization of two kinds of chaotic neural networks is derived. The proposed control method is efficient for implementing the synchronization when the parameters of the drive system are different from those of the response system. A numerical example is used to demonstrate the validity of the proposed method and the obtained result.

关键词： Chaotic system Neural networks Adaptive synchronization Linear matrix inequality

Direct Ion Beam Figuring Process and Rotational Measurement Method for Ultra-smooth Aspherical Surfaces of a 46.5 nm Telescope

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Research in Astronomy and Astrophysics 2023年第11期23卷 136-149页

作者： Weichen Gu Jun Yu Pengfeng Sheng Qiaoyu Wu Qiushi Huang ZhanShan Wang Key Laboratory of Advanced Micro-structured Materials Ministry of EducationTongji UniversityShanghai 200092China Institute of Precision Optical Engineering School of Physics Science and EngineeringTongji UniversityShanghai 200092China

This paper describes a fabrication process for the hyperboloidal concave mirror of a 46.5 nm telescope. The180 mm aperture hyperboloidal concave mirror and 70 mm aperture compensator are machined directly from chemical mechanical polishing of a spherical surface to a high-accuracy aspherical surface by ion beam figuring.The aspherical measurement method is the Dall null test. To minimize system errors in the measurement process,the rotational measurement method with six rotations is used in the null test. The results of the analysis for the ME(first solve the machined surface profile, then solve the system errors) and EM(first solve the system errors, then solve the machined surface profile) methods of calculation in the measurement are given. The ME method is a more accurate rotational test method, and the six rotations are appropriate for rotational measurements. After the figuring process, the hyperboloidal concave mirror surface profile reached 8.27 nm rms and the compensator surface profile is approximately 4 nm rms. The roughness of the hyperboloidal concave mirror is smooth to0.160 nm rms.

关键词： Astronomical Instrumentation Methods and Techniques instrumentation:high angular resolution telescopes

New delay-dependent criterion for the stability of recurrent neural networks with time-varying delay

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Science in China(Series F) 2009年第6期52卷 942-948页

作者： ZHANG HuaGuang wang zhanshan School of Information Science and Engineering Northeastern University Shenyang 110004 China

This paper is concerned with the global asymptotic stability of a class of recurrent neural networks with interval time-varying delay.By constructing a suitable Lyapunov functional, a new criterion is established to ensure the global asymptotic stability of the concerned neural networks, which can be expressed in the form of linear matrix inequality and independent of the size of derivative of time varying delay.Two numerical examples show the effectiveness of the obtained results.

关键词： recurrent neural networks global asymptotic stability linear matrix inequality （LMI） time-varying delay