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International Conference on automation and Computing (ICAC)

作者： Yunjia Zhang Dongliang Cui Weiqiang Wang Xubin Sun Zhiming Yuan Zhongbei Tian Xuewu Dai State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Shandong High-Speed Rail Transit Group Co. Ltd China School of Electronic and Information Engineering Beijing Jiaotong University Beijing China Signal and Communication Research Institute China Academy of Railway Sciences Corporation Limited Beijing China School of Engineering The University of Birmingham Birmingham UK Department of Mathematics Physics and Electrical Engineering Northumbria University Newcastle Upon Tyne UK

ISBN: (数字)9798350360882

ISBN: (纸本)9798350360899

Aiming at dynamic scheduling in multi-train timetable, a optimization model of multi-train timetable and speed profile optimization for energy conservation is proposed. The proposed approach integrates train operation trajectory optimization with the scheduling of arrival and departure times at stations. At each instance, the highest-priority train operation process is selected, and optimization is performed for the operation of only one train between stations. Various constraints are considered to ensure safe train operation and prevent conflicts with preceding trains. By collaboratively regulating and optimizing train arrival/ departure time, speed profile, traction/braking force, minimizing train traction energy consumption and minimizing power peak can be achieved. The objectives are combined into a single-objective nonlinear optimization problem through weighted summation, which is then solved using the differential evolution algorithm. The simulation verification conducted on the Yizhuang Line demonstrates that this method enables more efficient utilization of energy while also recovery from the delay. The train traction energy consumption was reduced by 11.35%. This work provides an important technical support and guidance for realizing the green, low-carbon and sustainable development of urban rail transit in the future.

关键词： Rails Energy consumption Optimization models Energy conservation Green products Dynamic scheduling Traction power supplies Delays Optimization Trajectory optimization

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Spectral Bisection Community Detection Method for Urban Road Networks

Spectral Bisection Community Detection Method for Urban Road...

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第40届中国控制会议

作者： Lu Guo Ying Cui Haili Liang Zhao Zhou Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and AutomationShanghai University Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and Technology

Coordination control of large-scale urban traffic networks provides a more easy and feasible way to improve mobility in heterogeneous city centers. Urban traffic network partitioning is the foundation and prerequisite for achieving regional *** order to describe the correlation strength between two adjacent intersections, a quantitative indicator considering the dynamic traffic flows is proposed to depict the congested degree in each link. Based on the simulation data collected from microscopic traffic model, the topology of urban traffic network could be converted into an adjacent matrix. Inspired by the concept of community detection in complex networks theory, spectral bisection method is utilized to find the spatial compactness areas in traffic networks. In addition, the modularity is adopted to evaluate the partitioning results and to point out the next partitioning direction at each step. The simulation is carried out for a peak hour in SUMO. Compared with other classical community detection methods, the proposed approach can obtain the adequate number of subnetworks with less computational complexity.

关键词： Complex Network Urban Road Networks Community Detection Spectral Bisection Method

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A Deep Neural Network-Assisted Diagnosis Method for Cardiovascular Disease Based on the Optimization of the TAdam Algorithm

A Deep Neural Network-Assisted Diagnosis Method for Cardiova...

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Chinese automation Congress (CAC)

作者： Yumei Hu Xing Li Yang Zhang Yuxuan Zhu Yuechao Sun College of Computer Science and Technology Dongguan University of Technology Dongguan China School of Electrical Engineering & Intelligentization Dongguan University of Technology Dongguan China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China School of Mechanical Engineering of DGUT Dongguan University of Technology Dongguan China Northeastern University College of Information Science and Engineering Northeastern University Shenyang China

Cardiovascular disease is a sudden and extremely disabling and deadly disease that hinders the development of public health care in China and poses a serious threat to the health of users. Therefore, this paper proposes a deep neural network-assisted diagnosis of cardiovascular disease based on TAdam algorithm optimization under a distributed medical monitoring network to enable rapid identification of cardiovascular patients, timely detection and reporting of the condition. This paper addresses the problems that deep neural network models are susceptible to the influence of their structure and hyperparameters and poor generalization convergence, firstly, the mainstream optimization algorithms based on deep learning are sorted out, and finally the T Adam algorithm is used to optimize the model. By comparing the common gradient optimization algorithms SGD (Stochastic Gradient Descent), Adagrad (Adaptive Gradient Algorithm), RMSprop (Root Mean Square propagation), Adam (Adaptive Moment Estimation) and the improved TAd am optimization algorithm trained and tested on the same dataset, the experimental results show that the TAdam algorithm exhibits the fastest convergence speed and the best generalization performance on the cardiovascular disease dataset. The method proposed in this paper enables rapid diagnosis of the user's disease risk and feedback to the relevant personnel to maximise user safety.

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Mean Square Consensus under Coopetitive Social Networks with Communication Noise

Mean Square Consensus under Coopetitive Social Networks with...

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第40届中国控制会议

作者： Hanzhe Cai Fanli Yuan Haili Liang Zhao Zhou Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and AutomationShanghai University Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and Technology

This paper aims to investigate a stochastic Altafini model, in which individuals are disturbed by the communication noise. We use coopetitive networks to describe their affiliation of classes. Different from the general situations with noises, when the opinion values in the classes converge, the noise will decrease. We consider the communication noise, when the differences of opinion values are larger, the influences of noise are greater. When the opinion values are reaching to biparite consensus,the influences of noise are decreasing, such a design is more in line with the reality. By constructing the appropriate Lyapunov function, the conditions for the stochastic stability of the system are obtained. We get the conclusion of mean square biparite consensus. In addition, numerical simulation results can verify the theoretical results.

关键词： Opinion dynamic Coopetitive networks Undirected graph Altafini model Communication noise

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Input-output finite-time sliding mode fault-tolerant control for Markovian jump systems with incomplete transition rates

Input-output finite-time sliding mode fault-tolerant control...

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Chinese Control and Decision Conference, CCDC

作者： Meng Zhao Haijuan Zhao Zhiru Cao Yugang Niu Ministry of Education The Key Laboratory of Smart Manufacturing in Energy Chemical Process (East China University of Science and Technology) Shanghai China School of Information and Control Engineering Qingdao University of Technology Qingdao China School of Mechatronic Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9781665478977

This paper deals with the input-output finite-time sliding mode control (SMC) problem of a class of uncertain Markovian jump systems with incomplete transition rates. It is assumed that the actuator failure may occur. A mode-dependent sliding surface is constructed. By synthesizing a fault-tolerant SMC scheme, the specified sliding surface can be reached in finite time. Furthermore, the input-output finite-time stability over both the reaching and sliding motion stages is ensured simultaneously by establishing some sufficient conditions. Finally, the developed fault-tolerant SMC approach is verified by a numerical example.

关键词： Fault tolerance Actuators Sufficient conditions Fault tolerant systems Resists Sliding mode control Numerical stability

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Investigation on Refractive Index Sensing Characteristics Based on Multimode Fiber Specklegram

SSRN

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SSRN 2022年

作者： Cai, Lu Wang, Min Zhao, Yong State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China College of Information Science and Engineering Northeastern University Shenyang110819 China Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology Qinhuangdao066004 China

In this paper, the refractive index (RI) sensing characteristic of single mode fiber (SMF)-multimode fiber (MMF) structure is investigated, and the two demodulation methods of specklegram and spectrum are compared experimentally. The results show that the RI resolution of the specklegram sensor is significantly higher than that of the optical spectrum analyzer (OSA). In addition, an SMF-no-core fiber (NCF)-MMF specklegram sensor is proposed. By extracting the eigenvalues of the gray-level co-occurrence matrix (GLCM) of the output specklegram, the image that the eigenvalue of the angular second moment changes with the NaCl solution that the addition of NCF increases the sensitivity from 0.797/RIU to 0.916/RIU. This specklegram sensor has good potential to achieve high-resolution RI detection. © 2022, The Authors. All rights reserved.

关键词： Refractive index

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Exponential Weighted Moving Average-Based Variational Mode Decomposition Method for Fault Diagnosis of Vehicle Batteries

Exponential Weighted Moving Average-Based Variational Mode D...

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Data Driven Control and Learning Systems (DDCLS)

作者： Penghao Wu Hongfeng Tao Engang Tian Tangwen Yin Hongtian Chen Yiyang Chen School of Mechanical and Electrical Engineering Soochow University Suzhou P. R. China Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan University Wuxi P. R. China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai P. R. China Department of Automation Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

In recent years, the rapid advancement of electric vehicles has heightened concerns regarding the safety of high-energy batteries. Consequently, there has been a significant focus on the development of fault diagnosis technologies for batteries. Intelligent fault diagnosis (IFD), particularly data-driven approaches, represents a crucial methodology in addressing this concern. This paper proposes a data-driven approach, for IFD in high-energy batteries utilized in electric vehicles. The proposed Exponentially Weighted Average Variational Mode Decomposition (EWVMD) method overcomes these limitations by employing the exponential weighted moving average (EWMA) technique to smooth collected time-series voltage data. This process reduces noise, accentuates abnormal change trends, and yields secondary data with enhanced features. Subsequently, variational mode decomposition (VMD) is applied to the secondary data. The resulting decomposed sub-mode curves (intrinsic mode functions - IMFs) and the change trends of the residual curve, in conjunction with a fault threshold tailored to actual working conditions, are utilized to ascertain the occurrence of faults. Design verification experiments, the C42MSA electric vehicle power supply battery undergoes charging and discharging tests with injected faults at fixed intervals. The collected fault signals are then subjected to fault diagnosis using EWVMD. Results demonstrate the algorithm's superior detection effectiveness and increased sensitivity to fault signals compared to traditional methods.

关键词： Fault diagnosis Learning systems Employee welfare Sensitivity Power supplies Noise Electric vehicles

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Silica Monolayer Isolation of Electrodeposited Sers Substrate and Online Probing of Molecule Adsorption Onto Mineral Microparticles in Relation to Flotation

SSRN

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SSRN 2023年

作者： Dong, Weinan Guo, Jinsheng Yu, Chun Guo, Bao Jiang, Kaixi School of Material Science and Engineering Fuzhou University Fujian Fuzhou350108 China State Key Laboratory of Process Automation in Mining & Metallurgy Zijin School of Mining and Geology Fuzhou University Fujian Fuzhou350108 China Fujian Normal University Fuzhou350117 China State Key Laboratory of Comprehensive Utilization of Low Grade Refractory Gold Ores Fujian Shanghang364200 China

In the minerals processing industry, the surface chemistry of mineral particles and its real-time detection can significantly enhance process performance, and ultimately leading to automotive and intelligent control. The adsorption of collector molecule onto bulk mineral specimens could be investigated with the help of shell-isolated nanoparticle enhanced Raman spectroscopy (SHINERS). However, this method is unsuitable for the online detection of particles fluid consisted of micro-sized chalcocite that encountered in industrial production processes. In this work, a novel strategy of Shell-Isolated Nanoparticles synthesis by electrodeposition of gold nanoparticles film and isolation of this film with crosslinked silica monolayer was proposed. The adsorption of 2-mercaptobenzothiazole (MBT), a typical flotation collector, onto a copper sulfide mineral, chalcocite was measured in-situ with the help of such a SERS substrate. Enhancement factors of 106~107 was calculated based on an idealized model. Furthermore, we discussed the stability of the silica isolation monolayer under high-power laser irradiation. © 2023, The Authors. All rights reserved.

关键词： Adsorption

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Application of Small Disturbance Instability Based on Random Response Surface Method in Wind Power System

Application of Small Disturbance Instability Based on Random...

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第40届中国控制会议

作者： Liu Yang Huaguang Zhang Zhiyun Gao College of Information Science and Engineering Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University the College of Information Science and Engineering Northeastern University

Based on the large-scale grid connection of wind power,this paper explores the correlation between the electromechanical oscillation and the random response of the power system by introducing stochastic differential and algebraic equations,and it concludes that the dynamic information of the power system really exists in the random *** the help of random average method,the introduction of parametric excitation and external excitation is a random *** the stability of the system,the joint probability density function and the stationary probability density function can explore the random bifurcation phenomenon of the *** this basis,the stochastic response surface method is applied to the investigation of small disturbance stability,and the stochastic power flow analysis is transformed into deterministic power flow analysis,which improves the calculation *** the method of selecting points based on the principle of linear independence,it is on the basis of ensuring *** the computational efficiency of SRSM is improved,when solving the problem of small disturbance stability control by introducing evaluation indicators,the problem of small disturbance stability is quantitatively analyzed,and the improved NSGA-algorithm is applied to regulate the disturbance caused by the active power adjustment of the *** improving the stability and adjustment rate of the system are verified by calculation examples to verify the feasibility of this method in practical applications,which provides a direction for future research and resolution of related problems.

关键词： Random response surface method small disturbance stability active power optimization adjustment

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Soft Sensing Model of Underflow Concentration for Thickener process based on Data Reconciliation 32

Soft Sensing Model of Underflow Concentration for Thickener ...

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32nd Chinese Control and Decision Conference, CCDC 2020

作者： Zhang, Hualu Wang, Fuli Zhang, Ihua He, Dakuo Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110004 China Northeastern University School of Information Science and Engineering Shenyang110004 China

ISBN: (纸本)9781728158549

Measured data in industrial production inevitably contain stochastic errors that are influenced by the environment and equipment, and the stochastic errors will reduce the accuracy of the measured data. Thickeners are widely used in mineral processing and sewage treatment, but the accuracy of the variables of the thickener process cannot meet the requirements, caused by the stochastic errors, and the underflow concentration cannot be real-time detected. So, pressure sensors were installed in the thickener to establish the soft sensing model of the underflow concentration, but the model accuracy is low owing to the stochastic errors of pressure values. This paper presents a soft sensing model of underflow concentration based on data reconciliation. The data reconciliation method is used to improve the accuracy of variables in thickener process, and then the soft sensing model of underflow concentration is established using the reconciled pressure. Applying the data of impact thickener process, the validity of the model is confirmed. © 2020 IEEE.

关键词： Stochastic systems

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