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Real-time traffic enhancement scheduling for train communication networks based on TSN

Journal of Traffic and Transportation Engineering(English Edition) 2025年第1期12卷 34-51页

作者： Deqiang He Zeqian Chen Daliang Sun Zhenzhen Jin Yanjun Chen Rui Ma Chen Liang Key Laboratory of Disaster Prevention and Structural Safety of Ministry of Education Guangxi Key Laboratory of Manufacturing System & Advanced Manufacturing TechnologySchool of Mechanical EngineeringGuangxi University

With the increasing data volume of train on-board system, real-time performance has become the most critical factor to ensure the safety of train operation. Considering that standard Ethernet cannot meet the real-time requirement of existing train communication network(TCN), the time-sensitive network(TSN) technology for TCN is introduced. To solve the time-delay problem, an adaptive switch queue selection mechanism for traffic scheduling is proposed. Firstly, the topology model of TCN based on TSN and the traffic model are described. Then, the K shortest path routing algorithm based on load balancing provides the optimal routing for the scheduling process. Finally, the adaptive switch queue selection mechanism is introduced to solve the aggregation flow conflict problem effectively, queue resources are properly allocated, and the gate control list(GCL) of each frame in the queue is obtained. Experimental results show that compared with the traditional constraint model, the schedulability of the model with an adaptive switch queue selection mechanism increases by 33.0%, and the maximum end-to-end delay and network jitter decrease by 19.1% and 18.6% on average respectively. It can provide theoretical support and application reference for the real-time performance optimization of TCN based on TSN.

关键词： Train communication network Time-sensitive network Adaptive switch queue selection mechanism Gate control list Real-time

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Automatic Control of Magnetic Helical Microrobots Docking with Target Objects in Liquid Environments

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Journal of Bionic Engineering 2025年第2期22卷 574-584页

作者： Fu Zhao Haoran Rong Lefeng Wang State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin150080China Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of EducationHarbin University of Science and TechnologyHarbin150080China

Bio-inspired magnetic helical microrobots have great potential for biomedical and micromanipulation applications. Precise interaction with objects in liquid environments is an important prerequisite and challenge for helical microrobots to perform various tasks. In this study, an automatic control method is proposed to realize the axial docking of helical microrobots with arbitrarily placed cylindrical objects in liquid environments. The docking process is divided into ascent, approach, alignment, and insertion stages. First, a 3D docking path is planned according to the positions and orientations of the microrobot and the target object. Second, a steering-based 3D path-following controller guides the helical microrobot to rise away from the container bottom and approach the target along the path. Third, based on path design with gravity compensation and steering output limits, alignment of position and orientation can be accomplished simultaneously. Finally, the helical microrobot completes the docking under the rotating magnetic field along the target orientation. Experiments verified the automatic docking of the helical microrobot with static targets, including connecting with micro-shafts and inserting into micro-tubes. The object grasping of a reconfigurable helical microrobot aided by 3D automatic docking was also demonstrated. This method enables precise docking of helical microrobots with objects, which might be used for capture and sampling, in vivo navigation control, and functional assembly of microrobots.

关键词： Magnetic actuation Helical microrobots Visual servo Motion control Docking

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Surface morphology generation mechanism of cortical bone longitudinal-torsional ultrasonic vibration assisted micro-milling

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Journal of manufacturing Processes 2025年 145卷 300-312页

作者： Gao, Peng Wang, Min Liang, Zhiqiang Gao, Xiangsheng Zan, Tao Beijing Key Laboratory of Advanced Manufacturing Technology Beijing University of Technology Beijing100124 China Key Laboratory of Fundamental Science for Advanced Machining Beijing Institute of Technology Beijing100081 China

Bone ultrasonic vibration micro-milling has an advantage of low cutting damage, and it potentially applied in minimally invasive medical surgery. However, cortical bone is a quasi-brittle biological material, and its cutting surface morphology generation mechanism are complex. Hence, this paper reveals the surface morphology generation mechanism of bone micro longitudinal-torsional ultrasonic assisted milling (LTUAM). The surface morphology generation of different cutting parameters in LTUAM was simulated. The bone ultrasonic vibration micro-milling experiments were carried out considering the bone transverse, across and parallel cutting directions. The surface morphology generation mechanism of cortical bone tissue in LTUAM was discussed. The experimental results indicated the crack propagation is strongly influenced by the micro-milling direction. The crack tends to propagate in parallel milling direction due to cement line cracking. The surface of bone in LTUAM has less damage and more smoother surface morphology. The bone LTUAM method effectively suppresses brittle fracture cutting, and reduces surface damage defects. This research provides efficient minimally invasive cutting methods and technical support for minimally invasive interventional surgical medical equipment. © 2025

关键词： Bone

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Collaborative optimization for multirobot manufacturing system reliability through integration of SysML simulation and maintenance knowledge graph

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Journal of manufacturing Systems 2025年 80卷 749-775页

作者： Zhou, Jian Zheng, Lianyu Wang, Yiwei School of Mechanical Engineering and Automation Beihang University Beijing100191 China MIIT Key Laboratory of Intelligent Manufacturing Technology for Aeronautics Advanced Equipments Ministry of Industry and Information Technology Beijing100191 China Beijing Key Laboratory of Digital Design and Manufacturing Technology Beijing100191 China

In the rapidly advancing field of industrial automation, the reliability and maintenance of multirobot manufacturing systems are crucial. This paper proposes a collaborative optimization method for the reliability of multirobot system, combining SysML (System Modeling Language) model simulation with an operational and maintenance knowledge graph, aiming to ensure the reliable operation of multirobot manufacturing systems. The SysML model provides a comprehensive framework to represent the system architecture, workflows, and key parameters, identify critical components and potential bottlenecks, and perform detailed reliability analysis. Simultaneously, by embedding intelligent algorithms, the operational and maintenance knowledge graph enables automatic detection of operational anomalies and intelligent generation of maintenance strategies for industrial robots. By integrating the SysML model with the operational and maintenance knowledge graph, a collaborative optimization framework for the reliability of multirobot system is constructed. This framework not only dynamically adjusts key parameters in the simulation model, enhancing the accuracy and real-time performance of system reliability assessments, but also optimizes maintenance strategies based on system simulation indicators to ensure the reliable operation of multirobot system. Case studies validate that the proposed method improves the reliability of multirobot manufacturing systems, demonstrating that the combination of SysML simulation and the operational and maintenance knowledge graph can effectively address the complexity of modern manufacturing systems, offering significant reference value. © 2025 The Society of manufacturing Engineers

关键词： Knowledge graph

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An algorithm for indoor positioning based on LightGBM + ExtraTrees chaotic weighted ensemble: evaluation and comparison

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Journal of Supercomputing 2025年第7期81卷 1-31页

作者： Zhang, Lieping Chen, Yao Gao, Xiaolin Zheng, Xinpeng Zhang, Cui Guangxi Key Laboratory of Special Engineering Equipment and Control Guilin University of Aerospace Technology Guilin China Key Laboratory of Advanced Manufacturing and Automation Technology Guilin University of Technology Guilin China School of Information Engineering Nanning College of Technology Guilin China

To address the issues of insufficient positioning accuracy and poor stability in existing indoor positioning algorithms, this paper proposes an indoor fingerprint positioning algorithm based on LightGBM and ExtraTrees chaotic weighted ensemble. First, the received signal strength indicator (RSSI) signal strengths of wireless fidelity (WiFi) at different locations are collected using a mobile device to construct a fingerprint database. Kalman filtering is then applied to preprocess the fingerprint data, removing outliers and noise to improve the data quality. The preprocessed dataset is subsequently divided into training and testing sets. Light gradient boosting machine (LightGBM) and extremely randomized trees (ExtraTrees) are used for modeling, and the chaos particle swarm optimization (CPSO) algorithm is employed to optimize the key parameters of both LightGBM and ExtraTrees. The optimal parameter configuration is determined based on comprehensive evaluation metrics. Finally, the optimal weight ratio of LightGBM and ExtraTrees models is determined through the CPSO algorithm for weighted fusion. Experimental results demonstrate that the proposed algorithm achieves an average positioning error of 1.1 m, which represents a reduction of 7.5–26.7% in average positioning error compared to LightGBM, ExtraTrees, and the LightGBM + ExtraTrees algorithms. After introducing random noise, the proposed algorithm exhibits the smallest variation in average positioning error, validating its significant advantages in positioning accuracy and anti-interference ability. However, the algorithm in this study is primarily based on static WiFi fingerprint data and has not yet been validated in dynamic environments. Future research should further explore its applicability and robustness in more complex environments. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Particle swarm optimization (PSO)

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An Iterative Tuning Method for Feedforward Control of Parallel Manipulators Considering Nonlinear Dynamics

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Chinese Journal of Mechanical Engineering 2025年第1期38卷 295-305页

作者： Xiaojian Wang Jun Wu Beijing Key Laboratory of Transformative High-end Manufacturing Equipment and Technology Tsinghua UniversityBeijing 100084China State Key Laboratory of Tribology in Advanced Equipment and Institute of Manufacturing Engineering Department of Mechanical EngineeringTsinghua UniversityBeijing 100084China

Feedforward control is one of the most effective control techniques to increase the robot’s tracking ***,most of the dynamic models used in the feedforward controllers are linearly simplified such that the nonlinear and time-varying characteristics of dynamics in the workspace are *** this paper,an iterative tuning method for feedforward control of parallel manipulators by taking nonlinear dynamics into account is *** on the robot rigid-body dynamic model,a feedforward controller considering the dynamic nonlinearity is *** iterative tuning method is given to iteratively update the feedforward controller by minimizing the root mean square(RMS)of the joint errors at each *** effectiveness and extrapolation capability of the proposed method are validated through the experiments on a 2-DOF parallel *** research proposes an iterative tuning method for feedforward control of parallel manipulators considering nonlinear dynamics,which has better extrapolation capability in the whole workspace of manipulators.

关键词： Parallel manipulator Dynamic model Feedforward control Iterative learning control Parameter design

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MoS2 synaptic transistor with one-step manufacture

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Science China(Information Sciences) 2025年第1期68卷 357-365页

作者： Yihao GUO Yang WANG Wenjie DENG Yi WU Jingtao LI Kexin LI Yuehui ZHAO Songlin YU Xiaoting WANG Yongzhe ZHANG Hui YAN Key Laboratory of Optoelectronics Technology of Education Ministry of China Faculty of Information TechnologyBeijing University of Technology Key Laboratory of Advanced Functional Materials Ministry of Education Faculty of Materials and ManufacturingBeijing University of Technology The 11th Research Institute of Electronics Technology Group Corporation

The synaptic transistor,which is a neuromorphic device with brain-like functions,has garnered significant attention due to characteristics such as low energy consumption,high integration,multiple functions,and high computational ***,the current synaptic transistor possesses a complicated structure and involves complex manufacturing steps,which is not conducive to low-cost,large-scale bionic ***,we introduce a simple MoS2synaptic transistor exhibiting robust synaptic *** transistor utilizes magnetron sputtering manufacture to combine the process of device metal electrode deposition and the introduction of defect states,which helps streamline the manufacturing process into a single *** long-term potentiation and long-term depression in photoelectric coordination are initially ***,biological functions,such as double pulse facilitation and the transformation behavior of short-term memory to long-term memory,are thoroughly evaluated,along with learning-forgetting-relearning ***,the device exhibits robust synaptic plasticity until incident light angles down to 30° to imitate the multi-to-one axon-cellular ***,a classical simulation of Pavlov's dog conditioned reflex is demonstrated along with the multiview extraction *** experimental results demonstrate a promising synaptic transistor with a simple structure,manufacturing technique,and excellent *** further indicates the potential for large-scale integration of bionic neuromorphic systems.

关键词： process optimization artificial synaptic device one-stepmanufacture synaptic plasticity bionic simulation

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Ultrafast Laser Irradiation Induced Oxidation of Dopant-Free Spiro-OMeTAD for Improving the Perovskite Solar Cells Performance

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Energy & Environmental Materials 2025年第2期8卷 288-294页

作者： Jiaqi Meng Xiangyu Chen Weihan Li Nianyao Chai Zhongle Zeng Yunfan Yue Fengyi Zhao Xuewen Wang Center of Femtosecond Laser Manufacturing for Advanced Materials and Devices State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology School of Materials Science and Engineering Wuhan University of Technology International School of Materials Science and Engineering Wuhan University of Technology National Energy Key Laboratory for New Hydrogen-Ammonia Energy Technologies Foshan Xianhu Laboratory

The exceptional photoelectric performance and high compatibility of perovskite materials render perovskite solar cells highly promising for extensive development,thus garnering significant *** perovskite solar cells,the hole transport layer plays a crucial *** the commonly employed organic small molecule hole transport material Spiro-OMeTAD,a certain period of oxidation treatment is required to achieve complete transport ***,this posttreatment oxidation processes typically rely on ambient oxidation,which poses challenges in terms of precise control and leads to degradation of the perovskite light absorption *** approach fails to meet the demands for high efficiency and stability in practical ***,the mechanism of ultrafast laser on Spiro-OMeTAD and the reaction process for laser-induced oxidation of it are ***2at Perovskite/Spiro-OMeTAD interface breaks down to produce I2upon ultrafast laser irradiation and I2promote the oxidation *** the laser irradiation oxidation processing,a higher stability of perovskite solar cells is *** work establishes a new approach toward oxidation treatment of Spiro-OMeTAD.

关键词： hole transport layer perovskite solar cells ultrafast laser irradiation undoped Spiro-OMeTAD

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Deep Reinforcement Learning-based Multi-Objective Scheduling for Distributed Heterogeneous Hybrid Flow Shops with Blocking Constraints

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Engineering 2025年第3期46卷 278-291页

作者： Xueyan Sun Weiming Shen Jiaxin Fan Birgit Vogel-Heuser Fandi Bi Chunjiang Zhang State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Institute of Automation and Information Systems Technical University of MunichGarching 85748Germany

This paper investigates a distributed heterogeneous hybrid blocking flow-shop scheduling problem(DHHBFSP)designed to minimize the total tardiness and total energy consumption simultaneously,and proposes an improved proximal policy optimization(IPPO)method to make real-time decisions for the DHHBFSP.A multi-objective Markov decision process is modeled for the DHHBFSP,where the reward function is represented by a vector with dynamic weights instead of the common objectiverelated scalar value.A factory agent(FA)is formulated for each factory to select unscheduled jobs and is trained by the proposed IPPO to improve the decision *** FAs work asynchronously to allocate jobs that arrive randomly at the shop.A two-stage training strategy is introduced in the IPPO,which learns from both single-and dual-policy data for better data *** proposed IPPO is tested on randomly generated instances and compared with variants of the basic proximal policy optimization(PPO),dispatch rules,multi-objective metaheuristics,and multi-agent reinforcement learning *** experimental results suggest that the proposed strategies offer significant improvements to the basic PPO,and the proposed IPPO outperforms the state-of-the-art scheduling methods in both convergence and solution quality.

关键词： Multi-objective Markov decision process Multi-agent deep reinforcement learning Proximal policy optimization Distributed hybrid flow-shop scheduling Blocking constraints

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Multi-UAV trajectory planning with field-of-view sharing mechanism in cluttered environments:application to target tracking

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Science China(Information Sciences) 2025年第5期68卷 89-102页

作者： Kai RAO Huaicheng YAN Penghui YANG Meng WANG Yunkai LV Key Laboratory of Smart Manufacturing in Energy Chemical Process of the Ministry of Education East China University of Science and Technology College of Machinery and Automation Weifang University

Multi-unmanned aerial vehicle(multi-UAV) target tracking requires coordinated trajectory planning that simultaneously ensures formation safety, target visibility, and motion smoothness. To address this challenge, we propose a distributed framework integrating heuristic-guided path search with spatiotemporal trajectory optimization. In the front end, each UAV constructs a safe area that accounts for both tracking distance and visibility considerations, and selects feasible expansion points for path search based on the desired tracking position. Subsequently, a unified trajectory optimizer is employed to derive an executable trajectory that complies with extensive constraints, predicated on the initial path configurations. Considering that UAVs may lose visibility of the target due to cluttered obstacles, a field-of-view sharing mechanism is proposed, enabling occluded UAVs to leverage teammates' visual data for robust collaborative planning in cluttered environments. Finally, simulations and comparative results are conducted through a visualization platform to validate the superior performance of the proposed multi-UAV trajectory planning framework for target tracking.

关键词： multi-UAV target tracking trajectory planning field-of-view sharing mechanism

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