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11th IEEE Data Driven control and Learning Systems Conference, DDCLS 2022

作者： Jia, Mingwei Liu, Yi Xu, Danya Yang, Tao Yao, Yuan Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China National Tsing Hua University Department of Chemical Engineering 30013 Taiwan

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

The development of an accurate data-driven fault diagnosis model faces several obstacles. One significant challenge is how to combine the model with the process mechanism rationally and improve the model interpretability. In this work, a fault diagnosis method based on a topology-informed graph convolutional network (TIGCN) is proposed. This model first uses the empirical knowledge that analyzes the operating state of the process and combines the operating data to construct a signed directed graph. Then the operating data is divided into three modalities in the time dimension. The model utilizes a well-designed spatial-temporal convolutional layer and signed directed graph to construct different modalities separately to effectively detect fault types. The superior fault diagnosis performance of the proposed TIGCN model is demonstrated on the Tennessee-Eastman process as compared to traditional approaches. © 2022 IEEE.

关键词： Failure analysis

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LEECAU-Net: A Latent Entropy-Quantized and Efficient Channel Attention-Aided U-Net Model for Microscopic Medical Image Segmentation 9

LEECAU-Net: A Latent Entropy-Quantized and Efficient Channel...

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9th IEEE International Conference on Progress in Informatics and Computing, PIC 2024

作者： Das, Sanchita Maity, Gouranga Mandal, Diptarka Kaplun, Dmitrii Voznesensky, Alexander Sarkar, Ram Jadavpur University Dept. of Cse Kolkata India Defence Instituite of Advanced Technology Department of Applied Mathematics Pune India Artificial Intelligence Research Institute China University of Mining and Technology Xuzhou China St. Petersburg Electrotechnical University 'LETI' Dept. of Automation and Control Process St. Petersburg Russia

ISBN: (纸本)9798350363203

Microscopic medical image segmentation is essential for detailed cellular-level analysis in computational pathology, offering insights into disease mechanisms. However, this task is particularly challenging due to the high similarity between different cellular classes and variability within each class, especially in densely packed or overlapping cell regions. To this end, we present LEECAU-Net (Latent Entropy-quantized and Efficient Channel Attention-aided U-Net), a U-Net-based model designed to improve segmentation accuracy through a dual-attention mechanism. Built on an Inceptionv4 backbone, LEECAU-Net's encoder integrates Latent Entropy-quantized Channel Attention (LECA) and Efficient Channel Attention (ECA) modules. The ECA module enhances the network's ability to focus on essential channel dependencies, while LECA leverages entropy quantification to prioritize channels rich in information, leading to better differentiation between similar structures. We have tested LEECAU-Net on three challenging publicly available datasets: Triple Negative Breast Cancer (TNBC), Multi-organ Nuclei Segmentation (MoNuSeg), and Cervical Nucleus Segmentation (CNS). Across these datasets, our model achieves higher performance metrics than numerous state-of-the-art approaches reported in the literature. The improved results underscore the effectiveness of LEECAU-Net's architecture in handling the complexity of microscopic medical images, making it a valuable tool for advancing automated cellular analysis in biomedical research. The source code and more results are made available at https://***/Cmatermedicalimageanalysis/LEECAU-Net. © 2024 IEEE.

关键词： Image segmentation

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Physics-guided graph learning soft sensor for chemical processes

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Chemometrics and Intelligent Laboratory Systems 2024年 249卷

作者： Liu, Yi Jia, Mingwei Xu, Danya Yang, Tao Yao, Yuan Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Chemical Engineering National Tsing Hua University Hsinchu300044 Taiwan

The surge in data-driven soft sensors for industrial processes is evident. However, most of them suffer from the limitation of being black-box models and this will hamper their widespread use. In response to this challenge, this study proposes a physics-guided graph-learning soft sensor that integrates a physical understanding of industrial processes by incorporating graph-based concepts with process physics. The soft sensor first constructs physical information based on causal relationships between variables using the conditional Granger causality test. Subsequently, it autonomously learns the unique sample information of each observation while employing a regularization loss to ensure the sparsity of the learned information. The model employs a two-stream structure for spatiotemporal encoding of both the physical and sample information. The modeling and prediction results on a penicillin fermentation process indicate that, using the proposed method, the knowledge gained from the data aligns with existing prior knowledge. This approach shows promise in filling the gap between data-driven and physics-based modeling in chemical processes. © 2024 Elsevier B.V.

关键词： Graphic methods

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automation of Technological processes for controlling Grain Moisture in the Flowu

Automation of Technological Processes for Controlling Grain ...

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Automatics and Informatics (ICAI), International Conference

作者： Palvan I. Kalandarov Shakhnoza R. Ubaydullayeva Rano T. Gaziyeva Nikola N. Nikolov Mariela I. Alexandrova Department “Automation and control of technology process in production” «Tashkent institute of irrigation and agricultural mechanization engineers» National Research University Tashkent Uzbekistan Department of Automation Faculty of Computer Science and Automation Technical University of Varna Varna Bulgaria

The paper deals with the problems of grain wounding requires large energy costs, requiring a multi-stage process of grain processing, installation and perfect and reliable automation systems for the storage and processing of raw materials, theoretical and experimental studies and the results of the use of the microwave method in measuring the moisture content of grain and grain materials. The method under consideration is based on the principle of selective absorption of microwave radiation energy by water in materials and its derivatives. By the degree of absorption of radiation, the concentration of moisture is judged. The paper investigates the amplitude and phase methods of the passing wave in free space. The influence of the elastic properties of the material under study on the electrical characteristics of the microwave wave, suggesting fundamentally new ways of measuring the attenuation and phase shift of the electromagnetic wave, including discrete conversion of the signal of the primary converter, which does not require rigid metrological support and the use of a phase shift, is substantiated. Information on the values of the thickness of the material is analyzed in order to correct the influence of this value, consisting of two parameters: the signal of the passing wave, the attenuation and phase shift which characterizes the humidity and the additional signal - the phase wave reflected from the front surface of the materials and carrying information about its thickness.

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Research and Analysis of the Method for Measuring the Moisture Content of Cottonmaterials at Ultrahigh Frequencies

Research and Analysis of the Method for Measuring the Moistu...

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Automatics and Informatics (ICAI), International Conference

作者： Palvan I. Kalandarov Khasan E. Turkmenov Shakhnoza R. Ubaydullayeva Nikola N. Nikolov Mariela I. Alexandrova Department “Automation and control of technology process in production” «Tashkent institute of irrigation and agricultural mechanization engineers» National Research University Tashkent Uzbekistan Department of Automation Faculty of Computer Science and Automation Technical University of Varna Varna Bulgaria

The article provides a theoretical analysis of the ultrahigh frequency (microwave) method of humidity measurement, discusses the problems of instrumentation of the method in question, and proposes a scheme of an experimental installation. Bulk cotton materials were selected as the objects of research. The electromagnetic wave radiation is analyzed during measurement and the evaluation of electrophysical characteristics requires the study of the functional dependence of the amplitude and phase shift on the mass ratio of humidity, mathematical models for various bulk cotton materials describing the joint effect of humidity, material density on the attenuation and phase shift of the passing wave are obtained.

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Design of Supervisory Model Predictive control for HVAC Systems and Two Zones with Consideration of Energy Efficiency and Thermal Comfort

Design of Supervisory Model Predictive Control for HVAC Syst...

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International Conference on control, automation and Systems ( ICCAS)

作者： Panithan Srisurapanon David Banjerdpongchai Department of Electrical Engineering Center of Excellence in Intelligent Control Automation for Process Systems Faculty of Engineering Chulalongkorn University Pathumwan Bangkok Thailand

This paper presents the design of supervisory model predictive control for HVAC systems and two zones. The supervisory control (SC) is designed to find the optimal reference temperature of each zone. The design criteria consist of the total operating cost (TOC) and the thermal comfort cost (TCC). Then, the model predictive control (MPC) is designed to track the optimal reference signals. When SC and MPC are designed for two zones simultaneously, they are referred to centralized SC and centralized MPC. On the other hand, when SC and MPC are designed for two zones separately, they referred to decentralized SC and decentralized MPC. We then compare the results between the decentralized control and the centralized control. The trade-off curve shows that the performance of centralized control is better than that of decentralized control. In particular, centralized MPC improves the performance in tracking reference signals. Furthermore, TOC of centralized control is lower than that of decentralized control. It can be concluded that the centralized control is appropriate for two zones in terms of the tracking of reference and the electrical charge.

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Study of Dynamic processes in Nonlinear Discrete Systems with Delay Based on Graph Models

Study of Dynamic Processes in Nonlinear Discrete Systems wit...

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2022 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2022

作者： Ubaydullayeva, Shakhnoza R. Yunusova, Sayyora Barno, Yeshmatova tashkent Inst. of Irrigation and Agricultural Mechanization Engineers National Research University Department 'Automation and Control of Technology Process in Production' Tashkent Uzbekistan Tashkent State Technical University Department Information Processing and Management Systems Tashkent Uzbekistan Tashkent State Technical University Department of Automation and Management of Technological Processes and Production Tashkent Uzbekistan

ISBN: (纸本)9781665483698

In connection with the problems of development and implementation of perfect automatic and automated control systems for complex technological processes based on modern information technology tools, the development of research methods for multidimensional nonlinear discrete control systems is of particular relevance. The variety of these systems is due to the types of modulation, non-linearities, modes of operation of impulse elements, characteristics of continuous parts. The article deals with the problems of modeling and research of one-dimensional and multidimensional pulse-frequency systems with delay based on the use of dynamic graphs. One of the key points in solving the problem is an approach based on the maximum consideration of the physical features of these systems. Given the structural complexity of systems, it is necessary first of all to establish the possibility of decomposing the system into simpler subsystems. Then the study of the system can be reduced to the study of individual subsystems and the nature of their interaction, that is, to the determination of the properties of the system as a whole by the properties of its elements. Systems with frequency-pulse modulation are essentially non-linear systems. The topological method based on dynamic graph models allows solving the fundamental difficulties of studying nonlinear discrete systems with delay, allows clearly and strictly formalizing their description, and makes it possible to obtain effective algorithms for analyzing one-dimensional and multidimensional systems of this class. The article presents an example of using the obtained algorithm. © 2022 IEEE.

关键词： Graph theory

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Multi-Agent control:A Graph-Theoretic Perspective

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Journal of Systems Science & Complexity 2021年第5期34卷 1973-2002页

作者： CHEN Fei REN Wei State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110004China School of Control Engineering Northeastern University at QinhuangdaoQinhuangdao 066004China. Department of Electrical and Computer Engineering University of CaliforniaRiversideCA 92521USA

Progress in development of multi-agent control is *** approaches for multiagent control,estimation,and optimization are discussed in a systematic way with particular emphasis on the graph-theoretic *** is paid to the design of multi-agent systems via Laplacian dynamics,as well as the role of the graph Laplacian spectrum,the challenges of unbalanced digraphs,and consensus-based estimation of graph *** emergent issues,e.g.,distributed optimization,distributed average tracking,and distributed network games,are also reported,which have witnessed extensive development *** are over 200 references listed,mostly to recent contributions.

关键词： Consensus cooperative control distributed average tracking distributed optimization multi-agent system

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Exponential Weighted Moving Average-Based Variational Mode Decomposition Method for Fault Diagnosis of Vehicle Batteries 13

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

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Wu, Penghao Tao, Hongfeng Tian, Engang Yin, Tangwen Chen, Hongtian Chen, Yiyang School of Mechanical and Electrical Engineering Soochow University Suzhou215137 China Jiangnan University Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Wuxi214122 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China

ISBN: (纸本)9798350361674

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. © 2024 IEEE.

关键词： Variational mode decomposition

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Data-Driven Distributionally Robust Planning of Energy Hub Coupled with Carbon Capture Utilization and Storage Facilities 42

Data-Driven Distributionally Robust Planning of Energy Hub C...

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42nd Chinese control Conference, CCC 2023

作者： Ma, Xutao Ning, Chao Shanghai Jiao Tong University Department of Automation Shanghai200240 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (纸本)9789887581543

Toward carbon peaking and carbon neutrality goals in China, a transition from traditional fossil power to renewable energy becomes an imperative need. This paper aims to address the planning problem of a highly renewable-energy penetrated energy hub system, coupled with carbon capture facilities and downstream production processes of hydrogen and methanol, under the uncertainty of renewable power output. To this end, we propose a two-stage distributionally robust optimal planning model, where investment decisions are the first-stage variables and operation variables are determined at the second stage after the realization of uncertainty. In the proposed model, we utilize historical data samples to construct a strengthened ambiguity set that leverages both Wasserstein distance and moment information for a better characterization of renewable generation uncertainty. Moreover, to efficiently solve the proposed planning problem, we develop a simplified affine decision rule method in a general setting with both moment and Wasserstein ambiguity, and then apply it to reformulate the distributionally robust planning problem. The derived reformulation possesses the favorable property that its scale is free from the sample size, thus greatly reducing the computational complexity. Computational results validate the effectiveness of the proposed planning model and the computational efficiency of the solution methodology. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Carbon capture

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