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A Congestion-Predicting Path Planning Algorithm for Narrow Lanes in Automated Warehouses 36

A Congestion-Predicting Path Planning Algorithm for Narrow L...

引用

36th Chinese control and Decision conference (CCDC)

作者： Hu, Junsong Yu, Botao Zhu, Baochang Wu, Weimin Zhejiang Univ Inst Cyber Syst & Control Hangzhou 310027 Peoples R China China Power Complete Equipment Co Ltd Beijing Peoples R China Noblelift Intelligent Equipment Co Ltd Huzhou Peoples R China

ISBN: (纸本)9798350387780;9798350387797

With the gradual development of intelligent logistics and multi-AGV (Automatic Guided Vehicle) systems, the application of automated warehouses is becoming more and more extensive. Among them, the path planning of AGVs is often a huge challenge. Under the specific constraints of road layout, the path planning methods described in the existing literature are often not good at avoiding congestion. In this paper, according to the limits of narrow lanes, we propose a path planning algorithm for predicting congestion. This algorithm is an improvement of the A-star algorithm, which introduces the current congestion cost and future congestion cost, and can plan the path to avoid the congested area, reduce the probability of runtime conflicts. Through simulation comparison, it is verified that the proposed algorithm has a good application prospect in alleviating traffic congestion.

关键词： Multi-AGV System narrow lanes path planning congestion predicting conflict-reducing

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Horizontal Path-following control Based on ESO for Parafoil systems with Error Constraint 6

Horizontal Path-following Control Based on ESO for Parafoil ...

引用

ieee 6th international conference on Industrial cyber-Physical systems (ICPS)

作者： Zhu, Erlin Du, Youwu Gao, Haitao Song, Wei Jiangsu Univ Technol Sch Elect & Informat Engn Changzhou Jiangsu Peoples R China Anhui Sci & Technol Univ Coll Elect & Elect Engn Bengbu Peoples R China

ISBN: (纸本)9798350311259

This paper investigates the problem of horizontal path-following control for parafoil systems with error constraint. Frist, by introducing the guidance theory, the horizontal position control is converted to the control of the azimuth angle of the parafoil system. The error signal of the angle is transformed to a new error variable, such that the error is constrained into the prescribed boundaries. Next, the methods of backstepping and output feedback are employed in the controller design. The uncertainties in parafoil system modeling and external disturbances are estimated using the lineaer extended state observer (LESO). The stability analysis based on Lyapunov method shows that all the error signals are uniformly ultimately bounded. Simulation results of a 6 degree-of-freedom parafoil system illustrate the effectiveness of the proposed method.

关键词： parafoil system path-following horizontal control error constraint LESO

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A Learning-based intelligent Method for Signature Forgery Detection using Pre-Trained Deep Models 2

A Learning-based Intelligent Method for Signature Forgery De...

引用

2nd international conference on intelligent cyber Physical systems and Internet of Things (ICoICI)

作者： Shirisha, N. Pranith, V. Penna Balaram, Allam Chowdary, M. Kalpana Shekar, Kukunoor MLR Inst Technol Comp Sci & Engn Hyderabad India

ISBN: (纸本)9798331540661;9798331540678

Signature of a person can uniquely identify the person and it is widely used in social situations and monetary transactions with individuals and financial entities. Many fraud cases have been appearing in society where signature of a person is forged for financial and other benefits. There is need for detecting forged signatures with technology driven approaches. With the emergence of Artificial Intelligence (AI), there are unprecedented possibilities in solving problems of the real world with responsible usage of AI. Deep learning (DL) is one part of AI which extends neural networks has become very significant in computer vision applications. From the existing approaches, it is observed that there is need for a complete framework for end to end processing of signatures for efficient detection of forgeries. Towards this end, we proposed a DL based framework for automatic detection of signature forgery. This study has proposed an algorithm known as Learning based Signature Forgery Detection (LbSFD), which exploits pipeline of multiple DL models such as CNN, VGG16 and Siamese. All the models are CNN variants used to improve efficiency in signature forgery detection. A benchmark signature dataset is used for our empirical study. Our experiments revealed that the CNN based models are highly efficient in signature forgery detection. Highest accuracy with 98.26% is achieved when VGG16 model is employed with transfer learning.

关键词： Signature Forgery Detection Artificial Intelligence Deep Learning Convolutional Neural Networks

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Digital Twins and BIM Technologies for Industrial systems Management

Digital Twins and BIM Technologies for Industrial Systems Ma...

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2024 international conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2024

作者： Mashtakov, Maxim M. Brusakova, Irirna A. Saint-Petersburg Electrotechnical University Etu 'LETI' Saint-Petersburg Russia

ISBN: (纸本)9798350395013

Modern trends in the management of industrial systems are consistent with the movement of society towards digitalization in the context of the transition to the technological structure of Industry 5.0. Of particular difficulty are projects for the implementation of digital twins of industrial systems, multidimensional data management technologies, implementation of data management visualization technologies, projects for organizing end-to-end data integration, projects for constructing digital images of processes, projects, objects, and implementation of artificial intelligence technologies. Project management for the implementation of modern digital technologies in the activities of enterprises is inextricably linked with the tasks of creating end-to-end data integration at all stages of IT project management. An industrial system is viewed as a cyber-physical system with the ability to control measurement information of technical and socio-economic subsystems in a single loop. An example is given of managing industrial automation of gas transportation enterprises using digital twin technology based on specialized software ChemSep and DWSIM. BIM technologies are used in a single control loop as supporting technologies in a single control loop for real objects. © 2024 ieee.

关键词： Data integration

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intelligent Monitoring and control of Power systems Based on Artificial Intelligence technology 11th

Intelligent Monitoring and Control of Power Systems Based on...

引用

11th international conference on Applications and Techniques in cyber Intelligence, ATCI 2023

作者： Wang, Lina Xu, Weidong Li, Xiaoxia Dongguan Power Supply Bureau of Guangdong Power Grid Corporation Guangdong Dongguan523000 China

intelligent monitoring and control of the power system plays an important role in saving the operating efficiency of the power system. However, the current intelligent monitoring and control of the power system has the problems of low stability, poor safety and insufficient reliability. Starting from artificial intelligence technology, the paper applies artificial intelligence Artificial Neural Network (ANN) and designs a power system intelligent monitoring and control model to adapt to the needs of smart power systems. The model applies adaptive learning to the power system through data analysis and pattern recognition methods. Experimental results show that the application of artificial neural networks in power systems can improve the real-time performance and accuracy of power systems, and its fault prediction accuracy can reach up to 98.9%. At the same time, it improves the system's data processing capabilities and adaptive capabilities. © 2024 The Authors. Published by Elsevier B.V.

关键词： Artificial Intelligence technology intelligent Detection and control Power systems System Security

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intelligent Adaptive Electric Vehicle Motion control for Dynamic Wireless Charging 26

Intelligent Adaptive Electric Vehicle Motion Control for Dyn...

引用

ieee 26th international conference on intelligent Transportation systems (ITSC)

作者： Das, Lokesh Chandra Dasgupta, Dipankar Won, Myounggyu Univ Memphis Dept Comp Sci Memphis TN 38152 USA

ISBN: (纸本)9798350399462

Dynamic wireless charging (DWC) is an emerging technology designed to enable electric vehicles (EVs) to be wirelessly charged while in motion. It is gaining significant momentum as it can potentially address the limited range problem for EVs. However, due to the significant power loss caused by wireless power transfer, improving the charging efficiency remains as a major challenge. This paper presents the first Long Short-Term Memory (LSTM)-based EV motion control system for DWC with an aim to maximize the charging efficiency. The dynamics of the electromagnetic field generated from the transmitter coils of a DWC system are effectively captured using a machine-learning approach based on the multi-layer LSTM. The multi-layer LSTM model is used to predict the location where the electromagnetic strength is expected to be maximal and to control the lateral position of EV accordingly to optimize the charging efficiency. Extensive simulations were conducted to demonstrate that our LSTM-based EV motion control system achieves by up to 174% higher charging efficiency compared with existing vehicle motion control systems focused on keeping an EV in the center of the lane.

关键词： Long short-term memory

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Observer-based Adaptive Sliding Mode control for Uncertain Stochastic systems with Bounded Transition Probabilities 1

Observer-based Adaptive Sliding Mode Control for Uncertain S...

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1st international conference on cyber-Energy systems and intelligent Energy, ICCSIE 2022

作者： Gao, Ziyuan Guo, Xinyu Sun, Yucheng Wang, Yingchun Northeastern University College of Information Science and Engineering Shenyang China

ISBN: (纸本)9781665452151

With constrained transition rates and matching uncertainties, the sliding mode control(SMC) issue of uncertain stochastic system is the focus of this study. This complex system is given an appropriate observer-based adaptive sliding mode controller. The system's state is first estimated using a Luenberger observer. Second, the sliding mode control approach ensures that Markovian jump systems (MJSs) with constrained transition rates and matching uncertainties are asymptotically stable. A numerical simulation is used to validate the results at the end. © 2023 ieee.

关键词： Sliding mode control

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Design, Modeling and Experimental Validation of Full-Vector-control-by-Wire Skateboard Chassis 22

Design, Modeling and Experimental Validation of Full-Vector-...

引用

22nd ieee international conference on Industrial Informatics, INDIN 2024

作者： Li, Quantong Wang, Xiangyu Li, Liang Lv, Haoyu Li, Zhaonan Fan, Zhixian School of Vehicle and Mobility Tsinghua University Beijing China College Of Engineering China Agricultural University Beijing China Bus Research Institute Zhongtong Bus Co. Ltd. Liaocheng China

ISBN: (纸本)9798331527471

intelligent vehicles are an emerging product of the combination of artificial intelligence technology and the modern automotive industry, and they are evolving into a new type of fully automated wheeled intelligent machine. However, the current control-by-wire chassis technology cannot meet the safety and flexibility requirements of future highly autonomous intelligent vehicles, necessitating the exploration of new perspectives and mechanisms to address current challenges. This paper proposes a novel Full-Vector-control-by-Wire Skateboard Chassis architecture, which integrates in-wheel motors, an omnidirectional steering system, an active suspension system, and an electromechanical braking system to design a drive-brake-steer-suspension integrated electric wheel solution. System dynamics modeling and controller design are carried out for the above new chassis architecture. By building an integrated electric wheel test bench and a skateboard chassis prototype, the feasibility of the proposed solution is validated. This paper provides experiential references for the development of next-generation intelligent control-by-wire chassis. © 2024 ieee.

关键词： Active suspension systems

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Test Lead Time And Cost Improvement Of Automotive Embedded Project - A New Perspective With automation And CI/CD

Test Lead Time And Cost Improvement Of Automotive Embedded P...

引用

2024 ieee international conference on Vehicular technology and Transportation systems, ICVTTS 2024

作者： Chatterjee, Tarun HARMAN International Intelligent Cockpit - Automation Test Bengaluru India

ISBN: (纸本)9798350355512

In recent years, automotive Original Equipment Manufacturers (OEMs) have been seeking cost-competitive, continuously upgradable, connected consumer electronics capabilities integrated into their Infotainment portfolio. Simultaneously, they are ambitious to achieve a release cycle ranging from half a year to a year. These expectations pose a major challenge for Infotainment Tier 1 vendors in terms of handling increased technical complexity while significantly reducing development, testing, and release time. This paper presents a proven approach to reducing test lead time using automation and Continuous Integration and Continuous Deployment (CI/CD). The approach was applied to a European OEM customer with a highly complex technology landscape and shorter software build release iterations. By implementing a logical software build generation process, creating test infrastructure, and deploying an end-to-end test stage, the described work model achieved significant test lead time reduction (approximately 10%), and cost reduction (around 7%) compared to traditional automation and CI/CD approaches. Furthermore, this concept can serve as a foundation for similar complex embedded products and projects, ensuring relevance to market demands in terms of release cycles and cost competitiveness. © 2024 ieee.

关键词： Competition

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Prediction of spraying process parameters based on BP neural network 12

Prediction of spraying process parameters based on BP neural...

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12th international conference on cyber technology in automation, control, and intelligent systems, cyber 2022

作者： Yu, Danyang Su, Chengzhi Yang, Dongxing Bao, Haifeng College of Artificial Intelligent Changchun University of Science and Technology Jilin China College of Mechanical and Electrical Engineering Changchun University of Science and Technology Jilin China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

In order to solve the problem that there are many process parameters in spraying process, which have complex influence on coating quality and have uncertain process parameters, a prediction method of spraying process parameters was proposed based on BP neural network algorithm. In the process of spraying, there are many factors that affect the quality of coating, and their interaction is complex, so it is difficult to find an accurate mathematical model in accordance with its rules. In this paper, BP neural network is used to establish the nonlinear mapping relationship between spraying process parameters and coating quality indexes, which is used as the prediction model of spraying process parameters. Taking ambient temperature, humidity, paint viscosity and film thickness as the input of neural network, and flow proportional valve pressure, atomization pressure and fan control pressure as the output, BP neural network model was established, and the prediction ability of the model was improved by optimizing the structure of the model. After optimizing the structure of BP neural network model, the prediction results show that the average relative error of flow proportional valve pressure is 0.4%. The average relative error of atomization pressure is 0.43%. The average relative error of sector control pressure is 0.61%. The established BP neural network model can meet the prediction requirements, and can clearly describe the relationship between environmental parameters, paint parameters, pressure parameters and coating quality, so as to better control the spraying process. © 2022 ieee.

关键词： Forecasting

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