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SSRN 2024年

作者： Zhang, Dingge Ma, Biao Yu, Liang Xu, Xiaoyu Wang, Liyong Zhang, Jinle School of Mechanical Engineering Beijing Institute of Technology Beijing100081 China School of Software Shandong University Shandong250101 China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100192 China China North Vehicle Research Institute Beijing100072 China

The dynamic characteristic investigation of powertrain system under time-varying conditions is highly relied on the dynamic torque signals of each component. However, methods that are sufficiently stable and efficient for obtaining these torque signals have not yet been realized. Thus, a five-dimensional digital twin system, including mechanism, behavior, geometric, statistical, and self-learning models, is established as a virtual mapping of physical system. These models are used to define solution methods, quantify characteristics, visualize displays, statistical analysis, and predict states, respectively. Then, a digital twin monitoring platform is established based on the virtual-real mapping, which can visualize dynamic characteristics of each component based on MQTT protocol. Moreover, the twin signals are verified from the perspectives of dynamics and kinematics through bench and real vehicle experiments, where the relative errors are less than 10%. In addition to the dynamic speed-torque signals of each component, twin signals also include jerk and sliding friction work used to evaluate the shifting quality. Through specific examples, it is demonstrated that the operating state for powertrain system can be monitored and evaluated based on all these twin signals, thus providing sufficient data support for further decision-making and feedback. © 2024, The Authors. All rights reserved.

关键词： Mapping

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A Method for Improving SLAM Localization Accuracy Based on Point-Line Feature

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SSRN 2023年

作者： Pei, Haodong Zhang, Jin Hong, Lu Zhang, Rui Li, Weishi Xia, Haojie School of Instrument Science and Opto-electronics Engineering Hefei University of Technology Hefei230009 China Anhui Province Key Laboratory of Measuring Theory and Precision Instrument Hefei230009 China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of Education Hefei230009 China

In this article, we propose a visual SLAM positioning accuracy improvement method based on point and line features. Our method leverages the perspective and photometric invariance of point features and the local gradient adaptability of line features to handle low-texture and repetitive-texture scenarios, where point features alone are not reliable. However, line features may suffer from endpoint uncertainty due to occlusion and other factors, which affects the re-projection error calculation based on their direction vectors. This leads to some line features degrading along the camera direction. To tackle this issue, we analyze the causes of line feature degradation and propose a method to identify and filter out these degraded line features. We evaluate our method on the TUM RGB-D benchmark and a real dataset and show that it can effectively reduce the trajectory error of visual SLAM based on point and line features. © 2023, The Authors. All rights reserved.

关键词： Textures

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Finite-Time Synchronization of Flux-controlled complex-Valued Memristive Neural Networks

Finite-Time Synchronization of Flux-Controlled Complex-Value...

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Neuromorphic Computing (ICNC), International Conference on

作者： Yonghuan Wang Leimin Wang Genping Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Wuhan Second Ship Design and Research Institute Wuhan China

In this paper, by using the flux-controlled memristor model, the finite-time synchronization problem of delayed complex-valued memristive neural networks (MCNNs) is studied. Firstly, according to the proposed memristor model, we model the MCNNs as continuous systems on voltage-flux-time $(\wp, \varpi, t)$ domain. Then, we design a class of approaches to realize state synchronization between the drive and response systems, and the corresponding synchronization conditions are achieved. Finally, the effectiveness of results is illustrated with the simulations.

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Optimal State Synchronization for Discrete-Time Nonlinear Multi-Agent Systems Under Switching Communication Graph

Optimal State Synchronization for Discrete-Time Nonlinear Mu...

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Industrial Cyber-Physical Systems (ICPS)

作者： Wenpeng He Xin Chen Sun Yipu Akinori Sekiguchi Jinhua She School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China School of Engineering Tokyo University of Technology Tokyo Japan

This paper proposes a new method to solve the optimal consensus control of discrete-time nonlinear multi-agent systems (MASs) under switching topology. To get a time-invariant control object for the switching MASs, a new augment local neighborhood tracking error is defined. Then the hierarchical control strategy is used to decompose the nonlinear consensus problems into two sub-problems, i.e., the tracking problems between individuals and the reference models, and the distributed consensus control among reference models and the leader. For the former, a robust ADHDP method is used to make the states of the follower track that of the reference model. For the latter, the value iteration method is used to derive the distributed optimal reference control. A simulation is given to verify the effectiveness of the proposed method.

关键词： Switches Transforms Consensus control Cyber-physical systems control systems Topology Synchronization

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Copper-Ceria Catalysts with Improved Water and Sulfur Resistance: Computational Design and Structural Optimization

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SSRN 2023年

作者： Sen, Shao You, Xiaoqing Li, Guoliang Wang, Shuxiao Key Laboratory for Thermal Science and Power Engineering Ministry of Education Tsinghua University Beijing100084 China Center for Combustion Energy Tsinghua University Beijing100084 China State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing100084 China Tsinghua University China

Copper species dispersed on ceria have emerged as promising catalysts for various energy and environmental applications. However, the presence of water vapor in the actual application environment can significantly hinder the catalyst activity. Flame-synthesized catalysts have been found to possess good water resistance as well as strong mercury oxidation and sulfur resistance. In this study, two types of copper-cerium binary structures were compared: Cu/CeO2 and CuO/CeO2, which represent highly dispersed copper on the CeO2 lattice surface (the main structure of the flame-synthesized catalyst) and CuO clusters supporting on the CeO2 lattice (the main structure of catalyst synthesized by impregnation methods), respectively. The adsorption energies of SO2, H2O, and Hg0 over these structures were studied by density functional theory calculations. The results revealed that Cu-O2/CeO2 (Cu/CeO2 with absorbed O2) had the highest Hg0 adsorption energy (-81.4 kJ/mol), followed by CuO/CeO2 (-13.1 kJ/mol) and CeO2 (-4.4 kJ/mol). Both Cu-O2/CeO2 and CuO/CeO2 showed improved sulfur resistance compared to CeO2, because SO2 was preferentially absorbed on copper sites, protecting the active sites on the CeO2 surface. H2O was absorbed and hydrolyzed into hydroxyl groups on the surfaces of all structures. The hydrolysis process consumed active oxygen on the CeO2 surface for CeO2 and CuO/CeO2, but consumed oxygen absorbed from the surrounding air for Cu-O2/CeO, leading to its best water resistance among the three. This finding opens up possibilities for the development of highly efficient and water-resistant catalysts. © 2023, The Authors. All rights reserved.

关键词： Density functional theory

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High Precision Tracking control Method Based on Model-Following control and Equivalent-Input-Disturbance

High Precision Tracking Control Method Based on Model-Follow...

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Intelligent Systems, International Workshop on

作者： Ruoyu Jiang Jinhua She School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Engineering Tokyo University of Technology Tokyo Japan

This paper presents a high-precision control method based on the model-following control (MFC) and equivalent-input-disturbance (EID) approaches. The MFC approach ensures that the output of the plant tracks the output of a desired nominal model. The EID estimates and eliminates an external disturbance. The combination of these two methods effectively achieves high-precision tracking. The validity of this method is demonstrated by a vibration-suppression example through simulations.

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Evaluation of Landslide Susceptibility Using Machine Learning Based on Information Value Sampling Method

Evaluation of Landslide Susceptibility Using Machine Learnin...

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Chinese Automation Congress (CAC)

作者： Lang Liu Xin Chen Lingran Zhao Weihua Cao School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China Exploration Institute of Geological Engineering of Xiangyang Xiangyang China

In landslide susceptibility prediction using machine learning (ML) models, the selection of appropriate negative samples significantly impacts the accuracy of the predictions. Many existing studies tend to randomly choose negative samples from the entire research area or specific attribute areas such as low slopes, leading to inaccuracies and biases that decrease the reliability of susceptibility mapping. To address this issue, this paper proposes an ML model based on the coupled information value (IV) method for susceptibility modeling. In this approach, the attribute values of environmental factors are transformed into information values, representing their contribution to landslides, using the information quantity method. Very low and low prone areas are then identified based on these information values, and random points are selected from these areas as negative samples for training and verifying subsequent machine learning models, which include the Random Forest (RF) model and Support Vector Machine (SVM) *** study focuses on the Three Gorges reservoir area in the Zigui-Badong area as an example. The comparative analysis of models trained using traditional sampling methods reveals that the RF model and SVM model, which were sampled using the information value method, achieve accuracies of 95.33% and 91.13%, respectively. In contrast, models trained using traditional sampling methods achieve accuracies of 90.43% and 88.69%, respectively.

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Target Tracking Algorithm Based on Occlusion Prediction

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SSRN 2023年

作者： Shang, Qing Zhang, Jin Yan, GuangZong Hong, Lu Zhang, Rui Xia, HaoJie School of Instrument Science and Opto-electronics Engineering Hefei University of Technology Hefei230009 China Anhui Province Key Laboratory of Measuring Theory and Precision Instrument Hefei230009 China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of Education Hefei230009 China

Occlusion and similar target interference are one of the most challenging scenes in visual target tracking tasks. At present, the target tracking algorithm based on the Siamese network framework often causes partial or complete loss of the target by using the maximum confidence location strategy. Aiming at the above problems, this paper designs a tracking method based on occlusion prediction and multi-peak response information fusion. At the same time, in order to reduce the interference of similar targets, a dynamically adjusted background suppression method is designed. First, the input image is processed by dynamic background suppression. Then, the maximum confidence point and local peak point are obtained by using the classification response map output by the network, and the final target position is obtained by fusing the occlusion prediction information and local peak point position information to correct the target position. The experimental results show that this method has a good effect in dealing with target occlusion interference. In the interference test based on OTB data set, applying this method to SiamBan and SiamGat can achieve a maximum tracking success rate of about 7% and a tracking accuracy improvement of 10%. © 2023, The Authors. All rights reserved.

关键词： Forecasting

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Industrial Cyber-Physical Systems (ICPS)

作者： Xiangxiang Zhang Wenkai Hu Ahmad W. Al-Dabbagh Weihua Cao School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Engineering The University of British Columbia Kelowna Canada

In industrial facilities, alarm systems are essential for process monitoring. However, due to the simplicity of alarm configuration and the poor performance of the alarm system, alarm floods often happen. Similarity analysis of alarm floods compares alarm flood sequences to look for common patterns. These patterns can offer information that is helpful in identifying root causes of alarm floods. Existing methods for alarm flood similarity analysis can only conduct similarity measures based on match operations for alarms represented by text strings; as a result, the match operations ignore the correlations between alarm occurrences. In this work, a new alarm flood similarity analysis method based on word embedding and Move-Split-Merge (MSM) distance is proposed, in order to reveal sequence similarity from a new perspective. The contributions are mainly twofold: 1) The correlations of alarm occurrences are considered in the alarm encoding via word embedding; 2) The MSM distance is calculated to analyze the similarity of alarm flood sequences of different lengths. Then, clustering results are compared with the original true labels of the alarm floods. The effectiveness of the proposed method is demonstrated by a case study with alarm data generated by a public industrial model of the Vinyl Acetate Monomer process.

关键词： Process monitoring Correlation Clustering algorithms Alarm systems Cyber-physical systems Industrial facilities Data models

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Multiplicative Fault Detection and Isolation in Dynamic Systems Using Data-Driven K-Gap Metric based kNN Algorithm

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IFAC-PapersOnLine 2022年第6期55卷 169-174页

作者： Caroline Charlotte Zhu Linlin Li Steven X. Ding Institute of Automatic Control and Complex Systems (AKS) University of Duisburg-Essen Duisburg 47057 Germany Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing 100083 Beijing China

In this paper, a fault detection and isolation scheme for multiplicative faults in dynamic systems based on data-driven K-Gap metric and k-nearest neighbour (kNN) classification is proposed. To detect multiplicative faults, the standard classification task of kNN is studied from the viewpoint of system analysis. To this end, the data-driven stable kernel representation based on input/output data is presented for feature extraction capturing the dynamic of linear time-invariant (LTI) systems. Data-driven K-Gap metric is used as an alternative tool for distance measure between two kernel subspaces in the kNN algorithm. A simulation example on the three-tank system (DTS200) demonstrates the successful detection and isolation of various multiplicative faults

关键词： Fault detection isolation multiplicative faults data-driven methods multiclass classification process monitoring K-Gap gap metrics

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