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arXiv 2023年

作者： Migórski, Stanislaw Bai, Yunru Zeng, Shengda College of Applied Mathematics Chengdu University of Information Technology Sichuan Province Chengdu610225 China School of Science Guangxi University of Science and Technology Guangxi Province Liuzhou545006 China Jagiellonian University in Krakow Faculty of Mathematics and Computer Science ul. Lojasiewicza 6 Krakow30348 Poland Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal University Guangxi Province Yulin537000 China

In this paper we consider an abstract class of time-dependent quasi variational-hemivariational inequalities which involves history-dependent operators and a set of unilateral constraints. First, we establish the existence and uniqueness of solution by using a recent result for elliptic variational-hemivariational inequalities in reflexive Banach spaces combined with a fixed-point principle for history-dependent operators. Then, we apply the abstract result to show the unique weak solvability to a quasistatic viscoelastic frictional contact problem. The contact law involves a unilateral Signorini-type condition for the normal velocity and the nonmonotone normal damped response condition while the friction condition is a version of the Coulomb law of dry friction in which the friction bound depends on the accumulated *** Codes 35J87, 47J20, 49J40, 49J45, 74G30, 74M15 © 2023, CC BY.

关键词： Friction

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Analysis of overload-based cascading failure in multilayer spatial networks

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Chinese Physics B 2020年第9期29卷 404-414页

作者： Min Zhang Xiao-Juan Wang Lei Ji Mei Song Zhong-Hua Liao School of Science Beijing University of Posts and TelecommunicationsBeijing 100876China School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation CenterBeijing 100854China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System EngineeringBeijing 100854China

Many complex networks in real life are embedded in space and most infrastructure networks are interdependent,such as the power system and the transport *** this paper,we construct two cascading failure models on the multilayer spatial *** our research,the distance l between nodes within the layer obeys the exponential distribution P(l)~exp(-l/ζ),and the length r of dependency link between layers is defined according to node *** entropy approach is applied to analyze the spatial network structure and reflect the difference degree between *** metrics,namely dynamic network size and dynamic network entropy,are proposed to evaluate the spatial network robustness and *** the cascading failure process,the spatial network evolution is analyzed,and the numbers of failure nodes caused by different reasons are also counted,***,we discuss the factors affecting network *** demonstrate that the larger the values of average degree,the stronger the network *** the length r decreases,the network performs *** the probability p is small,asζdecreases,the network robustness becomes more *** p is large,the network robustness manifests better performance asζ*** results provide insight into enhancing the robustness,maintaining the stability,and adjusting the difference degree between nodes of the embedded spatiality systems.

关键词： cascading failure multilayer network load distribution spatial network entropy

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MPC-based intelligent car for tobacco warehouse inspection

MPC-based intelligent car for tobacco warehouse inspection

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第40届中国控制会议

作者： Chao Ji Tian-Tian Luan Zhao-Jun Tang Ming-Xiao Sun Da-Xiu Cao School of Automation Harbin University of Science and Technology Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration Harbin University of Science and Technology Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin University of Science and Technology

In order to complete the inspection of tobacco storage warehouses economically and accurately, This article proposes a method of using a smart car to monitor temperature and humidity for 24 hours. The car with STM32 microcontroller as the main control chip, equipped with linear CCD sensor, ultrasonic obstacle avoidance module, as well as multiple detection sensors,UWB system, Wi Fi module, which can track and avoid obstacles automatically based on MPC, detect important parameter values in the tobacco storage warehouse for 24 hours and transmit date to the PC. It also has the function of real-time alarm and positioning using TDOA technology. After testing in a simulated environment, the car has been proven to accurately and reliably complete the detection of important parameters that affect tobacco mildew. Compared with traditional detection methods, this method is effective in tracing, comprehensive, easy to use and cost-effective. It can also be applied to other monitoring scenarios and has a wide range of application prospects.

关键词： MPC STM32 microcomputer Tobacco leaf mold detection Industrial intelligence

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Decision Tree Pruning Method Using Delayed Sampling

Decision Tree Pruning Method Using Delayed Sampling

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International Conference on Information Technologies (InfoTech)

作者： Sergei Alexandrovich Mitrofanov Eugene Stanislavovich Semenkin Department of System Analysis and Operations Research Institute of Informatics and Telecommunications Reshetnev Siberian State University of Science and Technology Krasnoyarsk Russian Federation Scientific and Educational Center "Artificial Intelligence Technologies" Bauman Moscow State Technical University Moscow Russian Federation Laboratory "Hybrid Methods of Modeling and Optimization in Complex Systems" Siberian Federal University Krasnoyarsk Russian Federation

ISBN: (数字)9798350365689

ISBN: (纸本)9798350365696

Algorithms based on decision trees have been around for quite some time, however, they are still one of the most popular because of their efficiency and the interpretability of their results. One of the main problems of decision trees is their high tendency to overfit. There are various ways to solve this problem, but this paper proposes a new method based on tree pruning using delayed sampling. The tree is trained using the Separation Measure and Differential Evolution algorithms. The proposed approach improves the standard method and is compared with it. The proposed approach demonstrates higher efficiency than the standard algorithm, and also improves the interpretability of the resulting trees.

关键词： Visualization Machine learning algorithms Accuracy Measurement uncertainty Machine learning Sampling methods Decision trees Stakeholders Information technology Standards

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Architecture analysis for avionics prognostics and health management system

Architecture analysis for avionics prognostics and health ma...

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Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS), CAA Symposium on

作者： Runfeng Chen Yang Hu Yanze Hou Qian Xuesen Laboratory of Space Technology China Academy of Space Technology (CAST) Beijing China Science and Technology on Complex Aviation System Simulation Laboratory 9236 Beijing China

ISBN: (纸本)9781665401166

Prognostics and Health Management (PHM) has been researched on for recent years, and extensive studies have been done on hot topics into this field, such as diagnostics, prognostics, and decision making. However, how to evaluate PHM system architecture is still lacking. This is particularly important when designing avionics system equipped with PHM functions. We propose a general, time-variant architecture model that can simulate PHM system. Performance metrics are calculated to quantitatively evaluate the system architecture. This is useful to find differences of architectures in the earlier design stage in engineering. A case study is presented of the use of architecture modelling to show the effectiveness. And future works are discussed.

关键词： Measurement Analytical models system performance Fault detection Decision making systems architecture Aerospace electronics

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A Multi-objective optimization model for simulation-based acquisition 7

A Multi-objective optimization model for simulation-based ac...

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7th IEEE International Conference on Progress in Informatics and Computing, PIC 2020

作者： Zhang, Xue Xue, Junjie Zhou, Junhua Shi, Guoqiang Yu, Yan Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing China Beijing Simulation Center Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing China

ISBN: (纸本)9781728170862

Large-scale equipment presents the characteristics of technology-intensive, knowledge-intensive and complex, which brings high investment and high risk to equipment acquisition. This paper analyzes the various components of equipment acquisition to fully apply modeling and simulation technology to each stage of it. On the basis of multi-objective optimization theory, the objective function of the lowest risk and lowest cost of simulation-based acquisition (SBA) is proposed. Then establishing a multi-objective optimization model for simulation-based acquisition according to the corresponding constraints. The nondominated sorting genetic algorithm II (NSGA II) and multi-objective particle swarm optimization (MOPSO) algorithms are used to optimize the model, and the majority voting method is used for integration. The comparison of simulation examples proves that the multi-objective optimization model oriented to SBA designed in this paper can effectively realize the optimization of each objective of SBA under cost constraints. And the feasibility and efficiency of optimization solution are guaranteed. © 2020 IEEE.

关键词： Multiobjective optimization

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Learning Latent Causal Factors from the Intricate Sensor Feedback of Contact-Rich Robotic Assembly Tasks

SSRN

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SSRN 2023年

作者： Chen, Yurou Yu, Jiyang Lin, Zhenyang Shen, Liancheng Liu, Zhiyong The State Key Lab of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China The Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai China Beijing Institute of Spacecraft System Engineering China Academy of Space Technology Beijing China

Achieving precise robotic assembly is paramount for safety and performance in industrial settings. Conventional assembly methods require tedious manual adjustment of many parameters, and it is challenging to meet the assembly requirements with tight clearance. Robot learning has been at the forefront of research, showing potential for automation and intelligence in robotic operations. However, intricate information such as force feedback is indispensable for high-precision robot assembly tasks, and current learning methods grapple with processing this complex observation data due to discontinuous force changes during operation and the inherent noise from the force sensor. To alleviate the low learning efficiency from the problematic observations, we propose introducing the concept of latent causal factors that cause the sensor observations and truly matter in assembly tasks. This paper analyses the impact of discontinuous and noisy observations and offers two ways to infer causal factors. Based on the implied latent factors, we propose a method that learns high-precision assembly policies from interacting with the environment. The algorithm's performance is evaluated in simulated and real-world nut assembly environments, demonstrating significant improvements over the previous methods. This research also underscores the promise of causal inference in addressing intricate industrial challenges%. © 2023, The Authors. All rights reserved.

关键词： Robotic assembly

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The Path Planning Algorithm for Uuv Based on the Fusion of Grid Obstacles of Artificial Potential Field

SSRN

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SSRN 2024年

作者： Sun, Mingxiao Xiao, Xiaotian Luan, Tiantian Zhang, Xiaoshuang Wu, Baoqi Zhen, Liqiang School of Automation Harbin University of Science and Technology No.52 Xuefu Road Nangang District Heilongjiang Province Harbin City150080 China Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration Harbin University of Science and Technology No.52 Xuefu Road Nangang District Heilongjiang Province Harbin City150080 China Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin University of Science and Technology No.52 Xuefu Road Nangang District Heilongjiang Province Harbin City150080 China Jiangsu Automation Research Institution No. 18 Shenghu Road Haizhou District Jiangsu Province Lianyungang City222000 China

The artificial potential field approach (APFA) has the advantages of short computation time and easy implementation, widely used in path planning. The problems of local oscillation and susceptibility to local minima for APFA are considered in three dimensions (3D) path planning application of unmanned underwater vehicle (UUV), and the artificial potential field grid method (APFG) is proposed. Firstly, the obstacles are rasterized in 3D map. The repulsive points are attached to the surface of the raster to change the repulsive influence range. This method can compensate for the long planning path caused by the idealization of traditional APFA modeling. At the same time, the repulsion function on the grid surface is changed so that the potential field on the grid surface is parallel to the grid surface, which will solve the local oscillation problem in the path planning of UUV. Then, virtual target points are introduced to avoid the UUV falling into local optimization. The simulations show that APFG effectively overcomes the shortcomings of local oscillations and the tendency to fall into local minima for UUV in 3D path planning, and the path planning is smooth and efficient. © 2024, The Authors. All rights reserved.

关键词： Motion planning

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Spirometer and sEMG respiratory patterns for clinical decision support system

Spirometer and sEMG respiratory patterns for clinical decisi...

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IEEE Instrumentation and Measurement technology Conference

作者： Amit Krishan Kumar Mansour H. Assaf Voicu Z. Groza Emil M. Petriu Faculty of Electrical-Electronic Engineering Duy Tan University Da Nang Vietnam Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing China School of Information Technology Engineering Mathematics and Physics The University of the South Pacific Suva Republic of Fiji School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada

To improve support system for subjects with respiratory ailments, this work analyses the respiratory patterns from spirometer and surface electromyography (sEMG). The patterns are integrated with risk and biochemical systems model to optimise the clinical decision support system (CDSS). The work considers terminal events for the spirometer and sEMG. The events and their associated patterns are correlated and projected on a hyperspace prior implementing it in decision support system. The proposed method shows that the different characteristics of breathing indicate some essential hidden information which when used as 4D scattered projection, optimises the decision making in CDSS. The analysis shows the effectiveness of bimodal respiratory patterns for different breathing capacities, which is promising for the modelled conditions.

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Zero-shot learning based on semantic embedding for ship detection 3

Zero-shot learning based on semantic embedding for ship dete...

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3rd International Conference on Unmanned systems, ICUS 2020

作者： Zhang, Zihan Zhoa, Jiajia Liang, Xinkai Northwestern Polytechnical University School of Electronics and Information Shaanxi Xi'an China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Bejing China

ISBN: (纸本)9781728180250

Zero-shot detection (ZSD) is a hot topic, which can detect unseen object without training on it. This new approach rises several challenges, e.g., the imbalance between positive and negative data, ambiguity between background and unseen classes, and how to align visual feature and semantic concept. In this paper, we apply an end-to-end zero-shot network to fulfil ZSD, where polarity loss is utilized to train detection model. polarity loss puts more importance on difficult data to reduce class imbalance and can maximize the difference between positive and negative predictions. Then, we use a semantic embedding method that use word vectors in both classification and regression subnets to better align visual features and semantic features. Finally, we use MS-COCO dataset as seen classes to train detection model, then we transfer the model for our own to detect warship object. Our model performs good on unseen classes and test accuracy of using polarity loss is apparently higher than that of using focal loss. © 2020 IEEE.

关键词： Zero-shot learning

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