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检索条件"任意字段=2023 6th International Conference on Advanced Algorithms and Control Engineering, ICAACE 2023"

共 292 条记录，以下是231-240 订阅

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Bounded Tracking of Uncertain Multiagent Systems with Time-Delays and Multiplicative Noises

Bounded Tracking of Uncertain Multiagent Systems with Time-D...

引用

Industrial Cyber-Physical Systems (ICPS)

作者： Guoliu Chen Xiaofeng Zong 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

this paper focuses on the bounded tracking control of general linear multi-agent systems(MASs), considering the effects of inevitable communication time-delays, measurement noises, and uncertain disturbances in practical applications. Firstly, the bounded tracking control problem of uncertain MASs under multiplicative noises is transformed into the boundedness problem of stochastic differential delay equations. then, the upper bound of agent tracking is calculated by means of linear variation, variation of constants formula and stochastic analysis theory, and sufficient conditions are given for the system to achieve the bounded tracking control.

关键词： Sufficient conditions Upper bound Uncertainty Measurement uncertainty Stochastic processes Cyber-physical systems Mathematical models

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Research on Path Planning control of Maze Robot

Research on Path Planning Control of Maze Robot

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international conference on Intelligent Autonomous Systems (ICoIAS)

作者： Minglu Chi Longchao Zhao Fuchao Yang Zhixiang Li Yahao Zhang Leichang Ma Xiaoyan Qian Qinchao Ren School of Intelligent Engineering Henan Institute of Technology Xinxiang China Xinxiang Aviation Industry (Group) Co. LTD Xinxiang China School of Economics Henan Institute of Technology Xinxiang China Jiangsu Huibo Robot Technology Co. LTD Suzhou China

To solve the problem of slow exploration speed of maze robot, a new kind of maze robot is designed in this paper. STM32FI03C8T6 with strong performance is used as the control chip to effectively improve the working efficiency of maze robot. the existing left-right exploration algorithms are compared and optimized, and the left-right cross algorithm is proposed, which effectively improves the maze exploration speed and accuracy of the maze robot. the experimental platform of the maze robot is built, and the path exploration and control program of the robot is verified. the results show that the designed maze robot can effectively explore the path, the hardware system can reduce the influence of external environmental factors such as light and temperature on the maze robot, and improve the motion control stability and exploration algorithm accuracy of the maze robot.

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Multi-view Clustering via Deep Graph Eembedding

Multi-view Clustering via Deep Graph Eembedding

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6th international conference on Intelligent Computing and Signal Processing (ICSP)

作者： Zeyu Huang Jiayao Wang Zhibiao Xue Shan Lin School of Information Engineering Chang’an University Xi’an China School of Electronics and Control Engineering Chang’an University Xi’an China

Due to the ability to analyze multi-view data with complex structure and sparse value, multi-view clustering has attracted increasing attention in recent years, among which graph-based methods have achieved impressive success. However, most of the current advanced methods obtain the clustering assignment on the unified similarity graph but ignored the latent information contained in the original data, which makes the clustering performance rely heavily on the quality of unified similarity graph. To overcome above drawback, we propose a multi-view deep clustering method based on Graph Convolutional Networks (GCN) called DGEMvC, which can mine deep embedding of the original data and optimize iterative clustering objectives. Firstly, for general type multi-view data, the necessary graph structure required by GCN is completed by the proposed cross-view similarity graph construction strategy. Secondly, the constructed similarity graph assists in mining the deep embedding of original data as auxiliary information. Significantly, we further design a novel strategy to generate a pseudo-label for each data point to realize the unsupervised learning pattern. Dozens experiments on six benchmark multi-view datasets verify that our proposed method is superior to other advanced multi-view algorithms and improves by 7% and 4% in ACC and NMI.

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Overview of Traction System Testing Indicators for Rail Transit Equipment 6th

Overview of Traction System Testing Indicators for Rail Tran...

引用

6th international conference on Electrical engineering and Information Technologies for Rail Transportation, EITRT 2023

作者： Liao, Jiaxin Xie, Zhengyu School of Traffic and Transportation Beijing Jiaotong University Beijing100044 China State Key Laboratory of Advanced Rail Autonomous Operation State Beijing Jiaotong University Beijing100044 China Key Lab of Proactive Safety and Risk Control in Railway Operation Beijing100044 China Beijing Research Center of Urban Traffic Information Sensing and Service Technologies Beijing100044 China

ISBN: (纸本)9789819993185

With the rapid development of China’s high-speed rail and other rail transit systems, the evaluation and quantitative assessment of traction performance have become increasingly significant. Traction systems, which are responsible for the propulsion of trains, play a crucial role in ensuring the efficiency, reliability, and safety of rail transportation. In this context, this study delves into the composition equipment and evaluation standards of traction systems, providing a valuable academic contribution to the design, manufacturing, and operation of new vehicle models. the paper extensively discusses the various components that constitute a traction system, including motors, control systems, power converters, and auxiliary equipment. It emphasizes the importance of evaluating the traction system’s performance and provides a comprehensive understanding of the evaluation criteria. Among these criteria, the paper focuses on three crucial aspects: no-load tests, load tests, and temperature rise *** addition to discussing the evaluation criteria for traction systems, the paper also introduces and explores the testing indicators specific to rail transit equipment. these indicators encompass factors such as tractive effort, energy efficiency, traction-to-weight ratio, and acceleration capability. By providing a comprehensive overview of these indicators, the paper offers valuable insights and guidance for researchers and practitioners in the field of rail transportation. © 2024, Beijing Paike Culture Commu. Co., Ltd.

关键词： Auxiliary equipment

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Remaining Useful Life Prediction of Aircraft Engines based on FA-SDAE-BiGRU

Remaining Useful Life Prediction of Aircraft Engines based o...

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international conference on Computer Network, Electronic and Automation (ICCNEA)

作者： Xiaojun Bai Yunpeng Sun Gong Meng School of Computer Science and Engineering Xi’an Technological University Xi’an China Beijing Aerospace Automatic Control Institution Beijing China

Aiming at the problems of insufficient feature extraction and inaccurate prediction in existing aircraft engines remaining useful life prediction algorithms, a fusion model based on feature attention mechanism, stacked noise reduction autoencoder and bidirectional gated cycle units (BiGRU) was proposed. Firstly, weight is assigned to each sensor data of aircraft engine by the feature attention mechanism, and new weight data is obtained. Next, the stack noise reduction autoencoder is used to extract the weighted data. then, bidirectional gated recurrent units are employed to predict the time series data and obtain the remaining useful life of the aircraft engine. To accurately select the hyperparameters of BiGRU, the Bayesian optimization algorithm is utilized for hyperparameter optimization. Finally, ablation experiments were conducted on the CMPASS dataset to validate the effectiveness of the proposed method, resulting in a root mean square error and score of 13.51 and 252.61, respectively.

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Dynamic Multi-Robot Path Planning in Narrow-Lane Environments with One-Way Constraint

Dynamic Multi-Robot Path Planning in Narrow-Lane Environment...

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international conference on Intelligent Autonomous Systems (ICoIAS)

作者： Zhenyu Song Ronghao Zheng Senlin Zhang Meiqin Liu College of Electrical Engineering Zhejiang University Hangzhou China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xian China

With the rapid development of the logistics industry, the path planning problem for automated guided vehicles (AGVs) in warehousing systems has become a prominent research topic. Traditional multi-robot path planning algorithms often perform poorly in narrow-lane environments found in warehouses. this paper proposes an improved dynamic multi-robot path planning algorithm specifically tailored for narrow-lane environments. By constraining the traversal directions within narrow lanes and dynamically determining the optimal directions, this algorithm achieves efficient multi-robot path planning and enhances the quality of robot paths. the effectiveness of the algorithm is theoretically proven in this paper. Extensive simulation data demonstrates that our algorithm efficiently generates high-quality paths in high-density narrow-lane warehouse environments.

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A Foreign Object Detection Method for Railway Overhead Lines Based on Few-Shot Learning 1

引用

6th international conference on Electrical engineering and Information Technologies for Rail Transportation, EITRT 2023

作者： Yu, Hang Qin, Yong Cao, Zhiwei Lian, Lirong Gao, Yang Bai, Jie Ge, Xuanyu State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University Beijing100044 China School of Traffic and Transportation Beijing Jiaotong University Beijing100044 China Key Laboratory of Railway Industry of Proactive Safety and Risk Control Beijing100044 China Beijing Rolling Stock Depot Beijing Group Co. Ltd Beijing100039 China

ISBN: (数字)9789819993192

ISBN: (纸本)9789819993185

It often occurs that foreign objects hang on railway overhead lines especially in windy days, which may lead to the delay of train, and even cause loss of life and property. With the gradual maturity of computer vision, railway foreign object detection has made great progress. this paper focuses on foreign object in railway overhead lines, and proposes a foreign object detection method based on few-shot learning. the proposed method consists of two stages: general training and fine-tuning training. In the first stage, the data-abundant common classes dataset is used to train the entire detector to obtain the underlying model parameters. In the fine-tuning stage, we make a balanced dataset consisting of common classes and enhanced railway classes, and fine-tune the last layer of the detector to accomplish few-shot foreign object detection. Finally, this proposed method is tested on images of overhead lines intrusions taken in actual railway scenario, and achieves 79% mAP in railway classes. © 2024, Beijing Paike Culture Commu. Co., Ltd.

关键词： Object detection

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Delay and Energy Consumption Optimization Method for Dependent Task Unloading

Delay and Energy Consumption Optimization Method for Depende...

引用

international conference on Computer Network, Electronic and Automation (ICCNEA)

作者： Xingxing Chou Wei Wang Wei Ren School of Electrical and Control Engineering Shaanxi University of Science and Technology Xi'an China

By deploying sufficient resources at the edge, applications with low latency and high energy consumption can be offloaded to the edge server for execution, reducing the total application execution cost. the existing unload models usually assume that several tasks of the application are independent of each other, and they often have dependencies in the real world. In view of the contradiction between the above research and reality, firstly, considering the limited edge server resources and battery capacity, this paper establishes a joint optimization model of delay and energy consumption (total cost) for dependent task unloading. Secondly, to solve this model problem, a Modified Sparrow Search Algorithm (MSSA) is proposed. To solve the problems of premature convergence, easy to fall into local optimal and poor global search ability in SSA, reverse learning, neighborhood search and Wolf pack algorithm are introduced to improve the algorithm. Finally, simulation results show that compared with other algorithms, the total application execution cost of the proposed algorithm is reduced by 7%~18%.

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6th international conference on Electrical engineering and Information Technologies for Rail Transportation, EITRT 2023

作者： Lian, Lirong Qin, Yong Cao, Zhiwei Gao, Yang Bai, Jie Ge, Xuanyu Yu, Hang State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University Beijing100044 China School of Traffic and Transportation Beijing Jiaotong University Beijing100044 China Key Laboratory of Railway Industry of Proactive Safety and Risk Control Beijing100044 China

ISBN: (数字)9789819993192

ISBN: (纸本)9789819993185

Real-time awareness of the service status of facilities and equipment in metro tunnels is essential for the safe movement of trains. For low illumination underground tunnel environments where objects have high similarity characteristics and are difficult to distinguish, this paper proposes a framework for tracking high similarity objects along the rail line based on on-board visual perception devices. the framework mainly consists of two stages: object detection and object association. In the first stage, an object detection algorithm is used to detect potentially faulty objects in the video, and this paper takes the continuous occurrence of insulated steel supports on the line as the high similarity research object. In the second stage a matching strategy is used to associate the same object in the video sequence and assign the same ID (identity document). Finally, the proposed framework was tested on metro tunnel video and achieved an accuracy of 95.64 and a detection performance of 25 FPS (frames per second), 82.17 MOTA (multiple object tracking accuracy) and 88.46 MOTP (multiple object tracking precision) tracking performance. © 2024, Beijing Paike Culture Commu. Co., Ltd.

关键词： Object detection

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Progress of Operation control System for EAST Neutral Beam Injector

Progress of Operation Control System for EAST Neutral Beam I...

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IEEE international conference on Automation, Electronics and Electrical engineering (AUTEEE)

作者： Renzhong Wang Yahong Xie Yuanzhe Zhao Institute of Plasma Physics Hefei Institutes of Physical Science Chinese Academy of Sciences University of Science and Technology of China Hefei China Institute of Plasma Physics Hefei Institutes of Physical Science Chinese Academy of Science Hefei China

the Experimental advanced Superconducting Tokamak (EAST) was constructed to explore the potential for steady-state nuclear fusion operation under long-pulse, high-performance conditions. Neutral Beam Injection (NBI) has been implemented to assist in heating the magnetically confined plasma during fusion reactions. the NBI control System (NBICS) is a distributed control system used for controlling the operation of NBI experiments. As more and more achievements are made, experiments based on EAST continue to evolve towards higher goals, which also impose stricter control requirements on NBI. To further ensure the efficiency of NBI control and injection, a new Operation control System (OCS) has been developed. the new system incorporates the latest features of Experimental Physics and Industrial control System (EPICS), significantly enhancing the robustness and safety of the experimental operation process compared to the past. It possesses strong scalability, fully meeting the requirements of EAST experiments. OCS consists of several components. It integrates technologies such as the PV Access (PVA) protocol and the Phoebus framework in EPICS, achieving functionalities like parameter processing, experimental flow control, exception monitoring, and cooperative control. In this paper, the architectural design and development of the OCS are introduced.

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