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Multi-Robot Task Allocation Using Multimodal Multi-Objective Evolutionary Algorithm Based on Deep Reinforcement Learning MIAO Zhenhua(苗镇华), HUANG Wentao(黄文焘), ZHANG Yilian(张依恋), FAN Qinqin(范勤勤) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 377-387.   DOI: 10.1007/s12204-023-2679-7 Abstract （478）      PDF（pc） （975KB）（217）       Knowledge map    Save The overall performance of multi-robot collaborative systems is significantly affected by the multirobot task allocation. To improve the effectiveness, robustness, and safety of multi-robot collaborative systems,a multimodal multi-objective evolutionary algorithm based on deep reinforcement learning is proposed in this paper. The improved multimodal multi-objective evolutionary algorithm is used to solve multi-robot task allocation problems. Moreover, a deep reinforcement learning strategy is used in the last generation to provide a high-quality path for each assigned robot via an end-to-end manner. Comparisons with three popular multimodal multi-objective evolutionary algorithms on three different scenarios of multi-robot task allocation problems are carried out to verify the performance of the proposed algorithm. The experimental test results show that the proposed algorithm can generate sufficient equivalent schemes to improve the availability and robustness of multirobot collaborative systems in uncertain environments, and also produce the best scheme to improve the overall task execution efficiency of multi-robot collaborative systems. Reference | Related Articles | Metrics | Comments（0）

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Multi-Agent Path Planning Method Based on Improved Deep Q-Network in Dynamic Environments LI Shuyi (李舒逸), LI Minzhe (李旻哲), JING Zhongliang∗ (敬忠良) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 601-612.   DOI: 10.1007/s12204-024-2732-1 Abstract （407）      PDF（pc） （1213KB）（186）       Knowledge map    Save The multi-agent path planning problem presents significant challenges in dynamic environments, primarily due to the ever-changing positions of obstacles and the complex interactions between agents’ actions. These factors contribute to a tendency for the solution to converge slowly, and in some cases, diverge altogether. In addressing this issue, this paper introduces a novel approach utilizing a double dueling deep Q-network (D3QN), tailored for dynamic multi-agent environments. A novel reward function based on multi-agent positional constraints is designed, and a training strategy based on incremental learning is performed to achieve collaborative path planning of multiple agents. Moreover, the greedy and Boltzmann probability selection policy is introduced for action selection and avoiding convergence to local extremum. To match radar and image sensors, a convolutional neural network - long short-term memory (CNN-LSTM) architecture is constructed to extract the feature of multi-source measurement as the input of the D3QN. The algorithm’s efficacy and reliability are validated in a simulated environment, utilizing robot operating system and Gazebo. The simulation results show that the proposed algorithm provides a real-time solution for path planning tasks in dynamic scenarios. In terms of the average success rate and accuracy, the proposed method is superior to other deep learning algorithms, and the convergence speed is also improved. Reference | Related Articles | Metrics | Comments（0）

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Arc and Droplet Behaviors in Horizontal Short-Arc Pulsed Gas Metal Arc Welding of 9%Ni Steel with ERNiCrMo-3 Welding Wire LIU Yiwei1 (刘轶玮), HUA Xueming1* (华学明), WU Dongsheng1 (吴东升), LI Fang1 (李芳), CAI Yan1 (蔡艳), WANG Huan2 (王欢), YANG Xiurong3 (杨修荣) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 361-376.   DOI: 10.1007/s12204-022-2548-9 Abstract （85）      PDF（pc） （5299KB）（119）       Knowledge map    Save Short-arc pulsed gas metal arc welding (P-GMAW) was used to solve the difficulties of molten pool spreading and droplet transfer of Ni-based welding wire. Suppression of short-circuit current was used to reduce spatter. Arc length stabilizer was used to acquire a proper and stable arc length maintained at the critical position where short circuit starts to occur. Short-arc P-GMAW with or without arc length stabilizer was compared. The droplet transfer, arc behaviors and weld bead profiles were investigated and compared based on the high-speed photography and observation of weld cross-section. When the arc length stabilizer was deactivated, the arc length was unstable and too short. The droplet transfer mode was mainly short circuit partial transfer, with only a small part of the droplet transferred into the molten pool, with the characteristics of no obvious necking, a few spatters, small droplet impact, long short circuit duration and high short-circuit current. There was also a small proportion of short circuit complete transfer with obvious necking, larger droplet impact, shorter short-circuit duration and lower short-circuit current. With arc length stabilizer, droplet transfer modes were short circuit complete transfer and spray transfer. The spray transfer had the largest droplet impact, no short circuit and no spatter. With the arc length stabilizer activated, a deep penetration, a high penetration ratio, a small reinforcement and a large reinforcement factor were acquired. This provides an innovative method to solve the difficulties of droplet transfer and molten pool spreading and eliminate the incomplete fusion in the GMAW of 9%Ni steel with nickel-based alloy welding wire. Reference | Related Articles | Metrics | Comments（0）

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Review on Anti-Frost Technology Based on Microchannel Heat Exchanger YE Zhenhong(叶振鸿), WANG Wei(王炜), LI Xinhua(李新华), CHEN Jiangping(陈江平) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 161-178.   DOI: 10.1007/s12204-022-2539-x Abstract （260）      PDF（pc） （4397KB）（104）       Knowledge map    Save Frosting is an inevitable adverse phenomenon in many fields such as industrial refrigeration, cryogenics, and heat pump air conditioning, which may influence the efficiency of the equipment and increase the energy consumption of the system. The complicated louvered-fin structure and fluid-channels arrangements of the microchannel heat exchanger (HEX) will affect the heat transfer performance and frosting characteristics. First, this article analyzes different factors such as refrigerant distribution, refrigerant flow pattern, and HEX surface temperature distribution. Further, combined with the features of the microchannel HEX, the existing anti-frosting technologies and various methods of surface treatment for anti-frosting are summarized. The review focuses on the preparation of superhydrophobic surfaces and their superior properties. Furthermore, the internal mechanism is analyzed in conjunction with the relevant research of our group. Superhydrophobic character has excellent anti-frosting performance and heat transfer performance, which is of great significance for improving energy-saving and system performance. Finally, the future development of superhydrophobic surface technology is analyzed and prospected. Reference | Related Articles | Metrics | Comments（0）

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Ship Pipe Layout Optimization Based on Improved Particle Swarm Optimization LIN Yan1, 2(林焰), BIAN Xuanyi1(卞璇屹), DONG Zongran3(董宗然) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 737-746.   DOI: 10.1007/s12204-022-2530-6 Abstract （189）      PDF（pc） （1456KB）（96）       Knowledge map    Save Ship pipe layout optimization is one of the difficulties and hot spots in ship intelligent production design. A high-dimensional vector coding is proposed based on the research of related pipe coding and ship pipe route features in this paper. The advantages of this coding method are concise structure, strong compatibility, and independence from the gridding space. Based on the proposed coding, the particle swarm optimization algorithm is implemented, and the algorithm is improved by the pre-selected path strategy and the branch-pipe processing strategy. Finally, two simulation results reveal that the proposed coding and algorithm have feasibility and engineering practicability. Reference | Related Articles | Metrics | Comments（0）

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Online Multi-Object Tracking Under Moving Unmanned Aerial Vehicle Platform Based on Object Detection and Feature Extraction Network LIU Zengmin (刘增敏), WANG Shentao(王申涛), YAO Lixiu(姚莉秀), CAI Yunze(蔡云泽) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 388-399.   DOI: 10.1007/s12204-022-2540-4 Abstract （219）      PDF（pc） （1105KB）（80）       Knowledge map    Save In order to solve the problem of small object size and low detection accuracy under the unmanned aerial vehicle (UAV) platform, the object detection algorithm based on deep aggregation network and high-resolution fusion module is studied. Furthermore, a joint network of object detection and feature extraction is studied to construct a real-time multi-object tracking algorithm. For the problem of object association failure caused by UAV movement, image registration is applied to multi-object tracking and a camera motion discrimination model is proposed to improve the speed of the multi-object tracking algorithm. The simulation results show that the algorithm proposed in this study can improve the accuracy of multi-object tracking under the UAV platform, and effectively solve the problem of association failure caused by UAV movement. Reference | Related Articles | Metrics | Comments（0）

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Anti-Occlusion Object Tracking Algorithm Based on Filter Prediction CHEN Kun(陈坤), ZHAO Xu(赵旭), DONG Chunyu(董春玉), DI Zichao(邸子超), CHEN Zongzhi(陈宗枝) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 400-413.   DOI: 10.1007/s12204-022-2484-8 Abstract （240）      PDF（pc） （5510KB）（80）       Knowledge map    Save Visual object tracking is an important issue that has received long-term attention in computer vision.The ability to effectively handle occlusion, especially severe occlusion, is an important aspect of evaluating theperformance of object tracking algorithms in long-term tracking, and is of great significance to improving therobustness of object tracking algorithms. However, most object tracking algorithms lack a processing mechanism specifically for occlusion. In the case of occlusion, due to the lack of target information, it is necessary to predict the target position based on the motion trajectory. Kalman filtering and particle filtering can effectively predict the target motion state based on the historical motion information. A single object tracking method, called probabilistic discriminative model prediction (PrDiMP), is based on the spatial attention mechanism in complex scenes and occlusions. In order to improve the performance of PrDiMP, Kalman filtering, particle filtering and linear filtering are introduced. First, for the occlusion situation, Kalman filtering and particle filtering are respectively introduced to predict the object position, thereby replacing the detection result of the original tracking algorithm and stopping recursion of target model. Second, for detection-jump problem of similar objects in complex scenes, a linear filtering window is added. The evaluation results on the three datasets, including GOT-10k, UAV123 and LaSOT, and the visualization results on several videos, show that our algorithms have improved tracking performance under occlusion and the detection-jump is effectively suppressed. Reference | Related Articles | Metrics | Comments（0）

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TshFNA-Examiner: A Nuclei Segmentation and Cancer Assessment Framework for Thyroid Cytology Image KE Jing1(柯晶), ZHU Junchao2 (朱俊超), YANG Xin1(杨鑫), ZHANG Haolin3 (张浩林), SUN Yuxiang1(孙宇翔), WANG Jiayi1(王嘉怡), LU Yizhou4(鲁亦舟), SHEN Yiqing5(沈逸卿), LIU Sheng6(刘晟), JIANG Fusong7(蒋伏松), HUANG Qin8(黄琴) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 945-957.   DOI: 10.1007/s12204-024-2743-y Abstract （148）      PDF（pc） （2836KB）（73）       Knowledge map    Save Examining thyroid fine-needle aspiration (FNA) can grade cancer risks, derive prognostic information, and guide follow-up care or surgery. The digitization of biopsy and deep learning techniques has recently enabled computational pathology. However, there is still lack of systematic diagnostic system for the complicated gigapixel cytopathology images, which can match physician-level basic perception. In this study, we design a deep learning framework, thyroid segmentation and hierarchy fine-needle aspiration (TshFNA)-Examiner to quantitatively profile the cancer risk of a thyroid FNA image. In the TshFNA-Examiner, cellular-intensive areas strongly correlated with diagnostic medical information are detected by a nuclei segmentation neural network; cell-level image patches are catalogued following The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) system, by a classification neural network which is further enhanced by leveraging unlabeled data. A cohort of 333 thyroid FNA cases collected from 2019 to 2022 from I to VI is studied, with pixel-wise and image-wise image patches annotated. Empirically, TshFNA-Examiner is evaluated with comprehensive metrics and multiple tasks to demonstrate its superiority to state-of-the-art deep learning approaches. The average performance of cellular area segmentation achieves a Dice of 0.931 and Jaccard index of 0.871. The cancer risk classifier achieves a macro-F1-score of 0.959, macro-AUC of 0.998, and accuracy of 0.959 following TBSRTC. The corresponding metrics can be enhanced to a macro-F1-score of 0.970, macro-AUC of 0.999, and accuracy of 0.970 by leveraging informative unlabeled data. In clinical practice, TshFNA-Examiner can help cytologists to visualize the output of deep learning networks in a convenient way to facilitate making the final decision. Reference | Related Articles | Metrics | Comments（0）

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Performance and Optimization of Air Source Heat Pump Water Heater with Cyclic Heating LI Fan(李凡), LU Gaofeng(陆高锋), DING Yunxiao(丁云霄), ZHENG Chunyuan(郑春元), LI Bin(李斌), ZHAI Xiaoqiang(翟晓强) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 179-187.   DOI: 10.1007/s12204-022-2500-z Abstract （183）      PDF（pc） （1349KB）（68）       Knowledge map    Save A new type of microchannel condenser applied in the air source heat pump water heater (ASHPWH) with cyclic heating was proposed in this study. The operating performance of the ASHPWH was first tested. Then,the structure of the microchannel condenser was optimized with the implement of vortex generators. Finally, a numerical model of the ASHPWH was established and the optimized microchannel condenser was studied. The experimental results showed that the average coefficient of performance (COP) of the 1 HP (735 W) ASHPWH reached 3.48. In addition, the optimized microchannel condenser could be matched with a 3 HP (2 430 W) ASHPWH with an average heating capacity of 10.30 kW, and achieving an average COP of 4.24, 14.6% higher than the limit value in the national standard. Reference | Related Articles | Metrics | Comments（0）

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Fault-Tolerant Dynamical Consensus of Double-Integrator Multi-Agent Systems in the Presence of Asynchronous Self-Sensing Function Failures WU Zhihai∗ (吴治海), XIE Linbo (谢林柏) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 613-624.   DOI: 10.1007/s12204-024-2716-1 Abstract （112）      PDF（pc） （540KB）（59）       Knowledge map    Save Double-integrator multi-agent systems (MASs) might not achieve dynamical consensus, even if only partial agents suffer from self-sensing function failures (SSFFs). SSFFs might be asynchronous in real engineering application. The existing fault-tolerant dynamical consensus protocol suitable for synchronous SSFFs cannot be directly used to tackle fault-tolerant dynamical consensus of double-integrator MASs with partial agents subject to asynchronous SSFFs. Motivated by these facts, this paper explores a new fault-tolerant dynamical consensus protocol suitable for asynchronous SSFFs. First, multi-hop communication together with the idea of treating asynchronous SSFFs as multiple piecewise synchronous SSFFs is used for recovering the connectivity of network topology among all normal agents. Second, a fault-tolerant dynamical consensus protocol is designed for doubleintegrator MASs by utilizing the history information of an agent subject to SSFF for computing its own state information at the instants when its minimum-hop normal neighbor set changes. Then, it is theoretically proved that if the strategy of network topology connectivity recovery and the fault-tolerant dynamical consensus protocol with proper time-varying gains are used simultaneously, double-integrator MASs with all normal agents and all agents subject to SSFFs can reach dynamical consensus. Finally, comparison numerical simulations are given to illustrate the effectiveness of the theoretical results. Reference | Related Articles | Metrics | Comments（0）

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Event-Triggered Fixed-Time Consensus of Second-Order Nonlinear Multi-Agent Systems with Delay and Switching Topologies XING Youjing1 (邢优靖), GAO Jinfeng1∗ (高金凤), LIU Xiaoping1, 2 (刘小平), WU Ping1 (吴平) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 625-639.   DOI: 10.1007/s12204-024-2695-2 Abstract （168）      PDF（pc） （1059KB）（58）       Knowledge map    Save To address fixed-time consensus problems of a class of leader-follower second-order nonlinear multiagent systems with uncertain external disturbances, the event-triggered fixed-time consensus protocol is proposed. First, the virtual velocity is designed based on the backstepping control method to achieve the system consensus and the bound on convergence time only depending on the system parameters. Second, an event-triggered mechanism is presented to solve the problem of frequent communication between agents, and triggered condition based on state information is given for each follower. It is available to save communication resources, and the Zeno behaviors are excluded. Then, the delay and switching topologies of the system are also discussed. Next, the system stabilization is analyzed by Lyapunov stability theory. Finally, simulation results demonstrate the validity of the presented method. Reference | Related Articles | Metrics | Comments（0）

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Motor Imagery Classification Based on Plain Convolutional Neural Network and Linear Interpolation LI Mingai1, 2∗ (李明爱), WEI Lina1 (魏丽娜) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 958-966.   DOI: 10.1007/s12204-022-2486-6 Abstract （89）      PDF（pc） （859KB）（58）       Knowledge map    Save Deep learning has been applied for motor imagery electroencephalogram (MI-EEG) classification in brain-computer system to help people who suffer from serious neuromotor disorders. The inefficiency network and data shortage are the primary issues that the researchers face and need to solve. A novel MI-EEG classification method is proposed in this paper. A plain convolutional neural network (pCNN), which contains two convolution layers, is designed to extract the temporal-spatial information of MI-EEG, and a linear interpolation-based data augmentation (LIDA) method is introduced, by which any two unrepeated trials are randomly selected to generate a new data. Based on two publicly available brain-computer interface competition datasets, the experiments are conducted to confirm the structure of pCNN and optimize the parameters of pCNN and LIDA as well. The average classification accuracy values achieve 90.27% and 98.23%, and the average Kappa values are 0.805 and 0.965 respectively. The experiment results show the advantage of the proposed classification method in both accuracy and statistical consistency, compared with the existing methods. Reference | Related Articles | Metrics | Comments（0）

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Explosion Hazard Analysis of Liquefied Petroleum Gas Transportation GAO Sida1 (高思达),HAO Lin 1* (郝琳), ZHU Zhenxing2* (朱振兴), WEI Hongyuan1 (卫宏远) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 252-260.   DOI: 10.1007/s12204-022-2536-0 Abstract （164）      PDF（pc） （1310KB）（53）       Knowledge map    Save This paper presents a quantitative risk analysis of liquefied petroleum gas (LPG) transportation. An accident that happened on June 13, 2020, on the highway near Wenling, China is studied as a case. In this accident, LPG carried by a tank truck on the highway leaked and caused a large explosion, which led to 20 deaths. Different methods are combined to calculate the consequence of the accident. Multi-energy model and rupture of vessel model are employed to calculate the overpressure; the simulation result of the multi-energy model is closer to the damage caused by the accident. The safety distances in accidents of LPG transport storage tanks of different capacities are calculated in this study; the results show that the damage of explosion will increase with the filling degree of the tank. Even though the filling degree is 90% (value required by law), the 99% fatality rate range will reach 42 m, which is higher than regulated distance between road and building. The social risk of the tank truck has also been calculated and the results show that the risk is not acceptable. The calculating method used in this study could evaluate the risk of LPG tanker more accurately, which may contribute to the establishment of transportation regulation so that losses from similar accidents in the future could be reduced. Reference | Related Articles | Metrics | Comments（0）

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Wind Speed Short-Term Prediction Based on Empirical Wavelet Transform, Recurrent Neural Network and Error Correction ZHU Changsheng(朱昶胜), ZHU Lina∗ (朱丽娜) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 297-308.   DOI: 10.1007/s12204-022-2477-7 Abstract （131）      PDF（pc） （1282KB）（51）       Knowledge map    Save Predicting wind speed accurately is essential to ensure the stability of the wind power system and improve the utilization rate of wind energy. However, owing to the stochastic and intermittent of wind speed, predicting wind speed accurately is difficult. A new hybrid deep learning model based on empirical wavelet transform, recurrent neural network and error correction for short-term wind speed prediction is proposed in this paper. The empirical wavelet transformation is applied to decompose the original wind speed series. The long short term memory network and the Elman neural network are adopted to predict low-frequency and highfrequency wind speed sub-layers respectively to balance the calculation efficiency and prediction accuracy. The error correction strategy based on deep long short term memory network is developed to modify the prediction errors. Four actual wind speed series are utilized to verify the effectiveness of the proposed model. The empirical results indicate that the method proposed in this paper has satisfactory performance in wind speed prediction. Reference | Related Articles | Metrics | Comments（0）

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Analysis of Software Trustworthiness Based on FAHP-CRITIC Method GAO Xiaotong11 (高晓彤), MA Yanfang1，2* (马艳芳), ZHOU Wei1 周伟) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 588-600.   DOI: 10.1007/s12204-022-2496-4 Abstract （71）      PDF（pc） （740KB）（50）       Knowledge map    Save Software trustworthiness includes many attributes. Reasonable weight allocation of trustworthy attributes plays a key role in the software trustworthiness measurement. In practical application, attribute weight usually comes from experts’ evaluation to attributes and hidden information derived from attributes. Therefore, when the weight of attributes is researched, it is necessary to consider weight from subjective and objective aspects. First, a novel weight allocation method is proposed by combining the fuzzy analytical hierarchy process (FAHP) method and the criteria importance though intercrieria correlation (CRITIC) method. Second, based on the weight allocation method, the trustworthiness measurement models of component-based software are established according to the seven combination structures of components. Third, the model reasonability is verified via proving some metric criteria. Finally, a case is carried out. According to the comparison with other models, the result shows that the model has the advantage of utilizing hidden information fully and analyzing the combination of components effectively. It is an important guide for measuring the trustworthiness measurement of component-based software. Reference | Related Articles | Metrics | Comments（0）

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Leader-Following Consensus of Multi-Agent Systems via Fully Distributed Event-Based Control GENG Zongsheng1 (耿宗盛), ZHAO Dongdong1,2 (赵东东), ZHOU Xingwen1 (周兴文), YAN Lei1 (闫磊), YAN Shi1,2∗ (阎石) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 640-645.   DOI: 10.1007/s12204-024-2718-z Abstract （107）      PDF（pc） （591KB）（49）       Knowledge map    Save This paper aims to study the leader-following consensus of linear multi-agent systems on undirected graphs. Specifically, we construct an adaptive event-based protocol that can be implemented in a fully distributed way by using only local relative information. This protocol is also resource-friendly as it will be updated only when the agent violates the designed event-triggering function. A sufficient condition is proposed for the leaderfollowing consensus of linear multi-agent systems based on the Lyapunov approach, and the Zeno-behavior is excluded. Finally, two numerical examples are provided to illustrate the effectiveness of the theoretical results. Reference | Related Articles | Metrics | Comments（0）

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Multi-Channel Based on Attention Network for Infrared Small Target Detection ZHANG Yanjun(张彦军), WANG Biyun(王碧云)，CAI Yunze (蔡云泽) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 414-427.   DOI: 10.1007/s12204-023-2616-9 Abstract （166）      PDF（pc） （1697KB）（48）       Knowledge map    Save Infrared detection technology has the advantages of all-weather detection and good concealment,which is widely used in long-distance target detection and tracking systems. However, the complex background,the strong noise, and the characteristics of small scale and weak intensity of targets bring great difficulties to the detection of infrared small targets. A multi-channel based on attention network is proposed in this paper, aimed at the problem of high missed detection rate and false alarm rate of traditional algorithms and the problem of large model, high complexity and poor detection performance of deep learning algorithms. First, given the difficulty in extracting the features of infrared multiscale and small dim targets, the multiple channels are designed based on dilated convolution to capture multiscale target features. Second, the coordinate attention block is incorporated in each channel to suppress background clutters adaptively and enhance target features. In addition, the fusion of shallow detail features and deep abstract semantic features is realized by synthesizing the contextual attention fusion block. Finally, it is verified that, compared with other state-of-the-art methods based on the datasets SIRST and MDFA, the proposed algorithm further improves the detection effect, and the model size and computational complexity are smaller. Reference | Related Articles | Metrics | Comments（0）

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Experimental Study and Numerical Simulation of Evacuation in an Offshore Platform ZHANG Jingjinga (张菁菁), ZHAO Jinchenga, b, c∗(赵金城), SONG Zhensena, b, c (宋振森), DUAN Lipinga, b, c(段立平) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 747-758.   DOI: 10.1007/s12204-023-2629-4 Abstract （114）      PDF（pc） （4007KB）（46）       Knowledge map    Save With the rapid development of marine oil and gas exploitation, the evacuation of offshore platforms has received more attention. First, an experimental investigation of the evacuation process of 120 participants in a real offshore platform is performed, and then simulation results provided by Pathfinder are validated against the measurement results. Second, four typical evacuation scenarios on the platform referring to IMO guidelines are investigated by Pathfinder with the speed values achieved in experiments. The simulation results show that both the utilization of exits and evacuation efficiency of people on the offshore platform need to be further improved. Last, the evacuation routes of people under the four scenarios are optimized, and the improvement of the evacuation performance after the optimization is evaluated by several mathematical indicators. Final results show that the evacuation with the optimized route design prompts the use efficiency of exits and further reduces the evacuation time. The present study provides a useful advice for potentially revising the IMO guidelines in future and provides efficient evacuation strategies for planning the emergency evacuation on offshore platforms. Reference | Related Articles | Metrics | Comments（0）

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Federated Approach for Privacy-Preserving Traffic Prediction Using Graph Convolutional Network LONARE Savita1，2* , BHRAMARAMBA Ravi2 J Shanghai Jiaotong Univ Sci    2024, 29 (3): 509-517.   DOI: 10.1007/s12204-021-2382-5 Abstract （124）      PDF（pc） （525KB）（41）       Knowledge map    Save Existing traffic flow prediction frameworks have already achieved enormous success due to large traffic datasets and capability of deep learning models. However, data privacy and security are always a challenge in every field where data need to be uploaded to the cloud. Federated learning (FL) is an emerging trend for distributed training of data. The primary goal of FL is to train an efficient communication model without compromising data privacy. The traffic data have a robust spatio-temporal correlation, but various approaches proposed earlier have not considered spatial correlation of the traffic data. This paper presents FL-based traffic flow prediction with spatio-temporal correlation. This work uses a differential privacy (DP) scheme for privacy preservation of participant’s data. To the best of our knowledge, this is the first time that FL is used for vehicular traffic prediction while considering the spatio-temporal correlation of traffic data with DP preservation. The proposed framework trains the data locally at the client-side with DP. It then uses the model aggregation mechanism federated graph convolutional network (FedGCN) at the server-side to find the average of locally trained models. The results of the proposed work show that the FedGCN model accurately predicts the traffic. DP scheme at client-side helps clients to set a budget for privacy loss. Reference | Related Articles | Metrics | Comments（0）

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New Lite YOLOv4-Tiny Algorithm and Application on Crack Intelligent Detection SONG Liboa (宋立博), FEI Yanqiongb (费燕琼) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 528-536.   DOI: 10.1007/s12204-022-2504-8 Abstract （120）      PDF（pc） （1358KB）（40）       Knowledge map    Save Conforming to the rapidly increasing market demand of crack detection for tall buildings, the idea of integrating deep network technology into wall climbing robot for crack detection is put forward in this paper. Taking the dependence and hardware requirements when deployed on such edge devices as Raspberry Pi into consideration, the Darknet neural network is selected as the basic framework for detection. In order to improve the inference efficiency on edge devices and avoid the possible premature over-fitting of deep networks, the lite YOLOv4-tiny algorithm is then improved from the original YOLOv4-tiny algorithm and its structure is illustrated using Netron accordingly. The images downloaded from Internet and taken from the buildings in campus are processed to form crack detection data sets, which are trained on personal computer with the AlexeyAB version of Darknet to generate weight files. Meanwhile, the AlexeyAB version of Darknet accelerated by NNpack package is deployed on Raspberry Pi 4B, and the crack detection experiments are carried out. Some characteristics, e.g., fast speed and lower false detection rate of the lite YOLOv4-tiny algorithm, are confirmed by comparison with those of original YOLOv4-tiny algorithm. The innovations of this paper focus on the simple network structure, fewer network layers, and earlier forward transmission of features to prevent over-fitting, showing the new lite neural network exceeds the original YOLOv4-tiny network significantly. Reference | Related Articles | Metrics | Comments（0）

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Multi-Objective Loosely Synchronized Search for Multi-Objective Multi-Agent Path Finding with Asynchronous Actions DU Haikuo1,2 (杜海阔), GUO Zhengyu3，4(郭正玉), ZHANG Lulu1,2(章露露), CAI Yunze1,2∗ (蔡云泽) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 667-677.   DOI: 10.1007/s12204-024-2744-x Abstract （125）      PDF（pc） （1177KB）（40）       Knowledge map    Save In recent years, the path planning for multi-agent technology has gradually matured, and has made breakthrough progress. The main difficulties in path planning for multi-agent are large state space, long algorithm running time, multiple optimization objectives, and asynchronous action of multiple agents. To solve the above problems, this paper first introduces the main problem of the research: multi-objective multi-agent path finding with asynchronous action, and proposes the algorithm framework of multi-objective loose synchronous (MOLS) search. By combining A∗ and M∗, MO LS-A∗ and MO-LS-M∗ algorithms are respectively proposed. The completeness and optimality of the algorithm are proved, and a series of comparative experiments are designed to analyze the factors affecting the performance of the algorithm, verifying that the proposed MO-LS-M∗ algorithm has certain advantages. Reference | Related Articles | Metrics | Comments（0）

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Toughening Mechanism of Large Heat Input Weld Metal for Marine Engineering Extra-Thick Plate LENG Junjie1 (冷俊杰), DI Xinjie,2*1 (邸新杰), LI Chengning1,2 (利成宁), CHENG Shanghua3 (程尚华) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 349-360.   DOI: 10.1007/s12204-023-2638-3 Abstract （97）      PDF（pc） （4684KB）（39）       Knowledge map    Save In order to study the latest designed large heat input welding material of marine engineering extrathick plate, EH36 steel was joined by using twin-wire submerged arc welding with heat inputs of 85, 100 and 115 kJ/cm separately. Meanwhile, the microstructure and mechanical properties were evaluated to explore the toughening mechanism of weld metal. Results show that a lot of active inclusions are obtained in the weld metal due to the design idea of low carbon and oxide metallurgy, which contributes to the generation of numerous fine and interlocking acicular ferrite. The acicular ferrite volume ratio of weld metal exceeds 60%. Moreover, the impact energy at −40 ◦C surpasses 115 J and the crack tip opening displacement value at −10 ◦C is more than 0.2 mm under three heat inputs owing to the role of acicular ferrite, of which 85 kJ/cm is the best. The martensiteaustenite constituents are minor in size and the microstructure of the weld metal in reheated zone is dominated by small massive equiaxed ferrite, without impairing the toughness. As the heat input increases, the content of acicular ferrite drops and then rises; the impact toughness and fracture toughness first worsen consequently and then stabilize on account of the dramatic expansion of the proeutectoid ferrite size. Reference | Related Articles | Metrics | Comments（0）

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Receding Horizon Control-Based Stabilization of Singular Stochastic Systems with State Delay WANG Xiaojing(王晓静),LIU Xiaohua(刘晓华), GAO Rong（高荣） J Shanghai Jiaotong Univ Sci    2024, 29 (3): 436-449.   DOI: 10.1007/s12204-022-2550-2 Abstract （71）      PDF（pc） （435KB）（39）       Knowledge map    Save For a class of discrete-time singular stochastic systems with multi-state delay, the stabilization problem of receding horizon control (RHC) is concerned. Due to the difficulty in solving the proposed optimization problem, the RHC stabilization for such systems has not been solved. By adopting the forward and backward equation technique, the optimization problem is solved completely. A sufficient and necessary condition for the optimization controller to have a unique solution is given when the regularization and pulse-free conditions are satisfied. Based on this controller, an RHC stabilization condition is derived, which is in the form of linear matrix inequality. It is proved that the singular stochastic system with multi-state delay is stable in the mean-square sense under appropriate assumptions when the terminal weighting matrix satisfies the given inequality. Numerical examples show that the proposed RHC method is effective in stabilizing singular stochastic systems with multi-state delay. Reference | Related Articles | Metrics | Comments（0）

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Pressure Pulse Response of High Temperature Molten Salt Check Valve Hit by Crystal Particles LI Shuxun (李树勋), SHEN Hengyun* (沈珩云), LIU Bincai (刘斌才),HU Yinggang (胡迎港), MA Tingqian (马廷前) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 271-279.   DOI: 10.1007/s12204-023-2601-3 Abstract （110）      PDF（pc） （2060KB）（38）       Knowledge map    Save In view of the problem that crystalline particles cause wall vibration at a low temperature, based on two-phase flow model, computational fluid dynamics is used to conduct the numerical simulation of internal flows when the valve openings are 20%, 60% and 100% respectively. The molten salt flow may be changed under strict conditions and produce forced vibration of the inner parts of molten salt particle shock valve body. Euler two-phase flow model is used for different molten salt sizes to extract temporal pressure pulse information and conduct statistical data processing analysis. The influence of the molten salt crystallization of molten salt particles on the flow and pressure pulse strength is analyzed. The results show that the crystallization of molten salt has a serious impact on the vibration of the valve body, especially in the throttle rate. The valve oscillation caused by the pressure pulsation mostly occurs from the small opening rate. As the opening increases, the pressure pulse threshold and its change trend decrease. Reference | Related Articles | Metrics | Comments（0）

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Multi-AGVs Scheduling with Vehicle Conflict Consideration in Ship Outfitting Items Warehouse DONG Dejin1,2 (董德金), DONG Shiyin3 (董诗音), ZHANG Lulu1,2 (章露露), CAI Yunze1,2∗ (蔡云泽) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 725-736.   DOI: 10.1007/s12204-024-2731-2 Abstract （109）      PDF（pc） （1452KB）（38）       Knowledge map    Save The path planning problem of complex wild environment with multiple elements still poses challenges. This paper designs an algorithm that integrates global and local planning to apply to the wild environmental path planning. The modeling process of wild environment map is designed. Three optimization strategies are designed to improve the A-Star in overcoming the problems of touching the edge of obstacles, redundant nodes and twisting paths. A new weighted cost function is designed to achieve different planning modes. Furthermore, the improved dynamic window approach (DWA) is designed to avoid local optimality and improve time efficiency compare to traditional DWA. For the necessary path re-planning of wild environment, the improved A-Star is integrated with the improved DWA to solve re-planning problem of unknown and moving obstacles in wild environment with multiple elements. The improved fusion algorithm effectively solves problems and consumes less time, and the simulation results verify the effectiveness of improved algorithms above. Reference | Related Articles | Metrics | Comments（0）

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Reward Function Design Method for Long Episode Pursuit Tasks Under Polar Coordinate in Multi-Agent Reinforcement Learning DONG Yubo1 (董玉博), CUI Tao1 (崔涛), ZHOU Yufan1 (周禹帆), SONG Xun2 (宋勋), ZHU Yue2 (祝月), DONG Peng1∗ (董鹏) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 646-655.   DOI: 10.1007/s12204-024-2713-4 Abstract （134）      PDF（pc） （567KB）（38）       Knowledge map    Save Multi-agent reinforcement learning has recently been applied to solve pursuit problems. However, it suffers from a large number of time steps per training episode, thus always struggling to converge effectively, resulting in low rewards and an inability for agents to learn strategies. This paper proposes a deep reinforcement learning (DRL) training method that employs an ensemble segmented multi-reward function design approach to address the convergence problem mentioned before. The ensemble reward function combines the advantages of two reward functions, which enhances the training effect of agents in long episode. Then, we eliminate the non-monotonic behavior in reward function introduced by the trigonometric functions in the traditional 2D polar coordinates observation representation. Experimental results demonstrate that this method outperforms the traditional single reward function mechanism in the pursuit scenario by enhancing agents’ policy scores of the task. These ideas offer a solution to the convergence challenges faced by DRL models in long episode pursuit problems, leading to an improved model training performance. Reference | Related Articles | Metrics | Comments（0）

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Iterative Model Predictive Control for Automatic Carrier Landing of Carrier-Based Aircrafts Under Complex Surroundings and Constraints ZHANG Xiaotian1(张啸天), HE Defeng1* (何德峰), LIAO Fei2 (廖飞) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 712-724.   DOI: 10.1007/s12204-023-2690-z Abstract （104）      PDF（pc） （1363KB）（37）       Knowledge map    Save This paper considers the automatic carrier landing problem of carrier-based aircrafts subjected to constraints, deck motion, measurement noises, and unknown disturbances. The iterative model predictive control (MPC) strategy with constraints is proposed for automatic landing control of the aircraft. First, the long shortterm memory (LSTM) neural network is used to calculate the adaptive reference trajectories of the aircraft. Then the Sage-Husa adaptive Kalman filter and the disturbance observer are introduced to design the composite compensator. Second, an iterative optimization algorithm is presented to fast solve the receding horizon optimal control problem of MPC based on the Lagrange’s theory. Moreover, some sufficient conditions are derived to guarantee the stability of the landing system in a closed loop with the MPC. Finally, the simulation results of F/A-18A aircraft show that compared with the conventional MPC, the presented MPC strategy improves the computational efficiency by nearly 56% and satisfies the control performance requirements of carrier landing. Reference | Related Articles | Metrics | Comments（0）

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Tree Detection Algorithm Based on Embedded YOLO Lightweight Network LV Feng(吕峰), WANG Xinyan* (王新彦), LI Lei(李磊), JIANG Quan(江泉), YI Zhengyang(易政洋) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 518-527.   DOI: 10.1007/s12204-022-2451-4 Abstract （142）      PDF（pc） （2443KB）（37）       Knowledge map    Save To avoid colliding with trees during its operation, a lawn mower robot must detect the trees. Existing tree detection methods suffer from low detection accuracy (missed detection) and the lack of a lightweight model. In this study, a dataset of trees was constructed on the basis of a real lawn environment. According to the theory of channel incremental depthwise convolution and residual suppression, the Embedded-A module is proposed, which expands the depth of the feature map twice to form a residual structure to improve the lightweight degree of the model. According to residual fusion theory, the Embedded-B module is proposed, which improves the accuracy of feature-map downsampling by depthwise convolution and pooling fusion. The Embedded YOLO object detection network is formed by stacking the embedded modules and the fusion of feature maps of different resolutions. Experimental results on the testing set show that the Embedded YOLO tree detection algorithm has 84.17% and 69.91% average precision values respectively for trunk and spherical tree, and 77.04% mean average precision value. The number of convolution parameters is 1.78 × 106, and the calculation amount is 3.85 billion float operations per second. The size of weight file is 7.11 MB, and the detection speed can reach 179 frame/s. This study provides a theoretical basis for the lightweight application of the object detection algorithm based on deep learning for lawn mower robots. Reference | Related Articles | Metrics | Comments（0）

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Establishment of Constraint Relation of Robot Dynamics Equation Based on Kinematic Influence Coefficients Method XU Yaru(徐亚茹), LI Kehong(李克鸿), SHANG Xinna（商新娜）, JIN Xiaoming(金晓明), LIU Rong(刘荣), ZHANG Jiancheng（张建成） J Shanghai Jiaotong Univ Sci    2024, 29 (3): 450-456.   DOI: 10.1007/s12204-023-2661-4 Abstract （80）      PDF（pc） （656KB）（36）       Knowledge map    Save Due to the diversity of work requirements and environment, the number of degrees of freedom (DOFs) and the complexity of structure of industrial robots are constantly increasing. It is difficult to establish the accurate dynamical model of industrial robots, which greatly hinders the realization of a stable, fast and accurate trajectory tracking control. Therefore, the general expression of the constraint relation in the explicit dynamic equation of the multi-DOF industrial robot is derived on the basis of solving the Jacobian matrix and Hessian matrix by using the kinematic influence coefficients method. Moreover, an explicit dynamic equation with general constraint relation expression is established based on the Udwadia-Kalaba theory. The problem of increasing the time of establishing constraint relationship when the multi-DOF industrial robots complete complex task constraints is solved. With the SCARA robot as the research object, the simulation results show that the proposed method can provide a new idea for industrial robot system modeling with complex constraints. Reference | Related Articles | Metrics | Comments（0）

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Data Augmentation of Ship Wakes in SAR Images Based on Improved CycleGAN YAN Congqiang1,2 (鄢丛强), GUO Zhengyun3,4 (郭正玉), CAI Yunze1,2∗∗ (蔡云泽) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 702-711.   DOI: 10.1007/s12204-024-2746-8 Abstract （135）      PDF（pc） （1418KB）（36）       Knowledge map    Save The study on ship wakes of synthetic aperture radar (SAR) images holds great importance in detecting ship targets in the ocean. In this study, we focus on the issues of low quantity and insufficient diversity in ship wakes of SAR images, and propose a method of data augmentation of ship wakes in SAR images based on the improved cycle-consistent generative adversarial network (CycleGAN). The improvement measures mainly include two aspects: First, to enhance the quality of the generated images and guarantee a stable training process of the model, the least-squares loss is employed as the adversarial loss function; Second, the decoder of the generator is augmented with the convolutional block attention module (CBAM) to address the issue of missing details in the generated ship wakes of SAR images at the microscopic level. The experiment findings indicate that the improved CycleGAN model generates clearer ship wakes of SAR images, and outperforms the traditional CycleGAN models in both subjective and objective aspects. Reference | Related Articles | Metrics | Comments（0）

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Numerical Investigation on Dynamic Response Characteristics of Fluid-Structure Interaction of Gas-Liquid Two-Phase Flow in Horizontal Pipe WANG Zhiwei(王志伟), HE Yanping(何炎平), LI Mingzhi（李铭志）, QIU Ming(仇明), HUANG Chao(黄超), LIU Yadong（亚东），WANG Zi(王梓) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 237-244.   DOI: 10.1007/s12204-022-2469-7 Abstract （128）      PDF（pc） （1576KB）（36）       Knowledge map    Save Fluid-structure interaction (FSI) of gas-liquid two-phase flow in the horizontal pipe is investigated numerically in the present study. The volume of fluid model and standard k-ε turbulence model are integrated to simulate the typical gas-liquid two-phase flow patterns. First, validation of the numerical model is conducted and the typical flow patterns are consistent with the Baker chart. Then, the FSI framework is established to investigate the dynamic responses of the interaction between the horizontal pipe and gas-liquid two-phase flow. The results show that the dynamic response under stratified flow condition is relatively flat and the maximum pipe deformation and equivalent stress are 1.8 mm and 7.5 MPa respectively. Meanwhile, the dynamic responses induced by slug flow, wave flow and annular flow show obvious periodic fluctuations. Furthermore, the dynamic response characteristics under slug flow condition are maximum; the maximum pipe deformation and equivalent stress can reach 4 mm and 17.5 MPa, respectively. The principal direction of total deformation is different under various flow patterns. Therefore, the periodic equivalent stress will form the cyclic impact on the pipe wall and affect the fatigue life of the horizontal pipe. The present study may serve as a reference for FSI simulation under gas-liquid two-phase transport conditions. Reference | Related Articles | Metrics | Comments（0）

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Working Fluid Distribution and Charge Regulation Control in Organic Rankine Cycle YE Zhenhong(叶振鸿), WANG Wei(王炜), LI Xinhua(李新华), CHEN Jiangping(陈江平) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 188-201.   DOI: 10.1007/s12204-022-2538-y Abstract （184）      PDF（pc） （1116KB）（36）       Knowledge map    Save Charge-based studies, in particular investigations of mass distribution, are still almost absent, although the efficiency of the organic Rankine cycle (ORC) has attracted a great deal of scholarly attention. This paper aims to provide a new perspective on the intrinsic relationship among the mass distribution, phase-zone distribution in the heat exchanger (HEX), charge of working fluid (WF), rotation speed of the pump (RSP), and system performance. A comprehensive ORC simulation model is presented by linking each component’s sub-models, including the independent models for HEX, pump, and expander in an object-oriented fashion. The visualization study of mass distribution of the WF in the system is investigated under different working conditions. Furthermore, the volume and mass of the gas phase, two-phase and liquid phase of WF in the HEX and their variation rules are analyzed in-depth. Finally, the strategies of charge reduction considering HEX areas and pipe sizes are investigated. The results show that the model based on the interior-point method provides high levels of accuracy and robustness. The mass ratio of the WF is concentrated in the liquid receiver, especially in the regenerator, which is 32.9% and 21.9% of the total mass, respectively. Furthermore, 2.4 kg (6.9%) WF in the system gradually migrates to the hightemperature side as the RSP increases while 6.1 kg (17.4%) WF migrates to the low-temperature side, especially to the condenser, as the charge in the system increases. Output power and efficiency both decrease gradually after the peak due to changes in RSP and charge. Last, reducing heat transfer areas of the condenser and regenerator is the most effective way to reduce WF charge. Reference | Related Articles | Metrics | Comments（0）

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Numerical Study on Comparison of Negative and Positive Surface Discharge in c-C4F8/CF3I/CO2 Gas Mixture FAN Binhai(范彬海), ZHOU Xiaoli(周小丽), QIAN Yong(钱勇), ZANG Yiming(臧奕茗) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 202-215.   DOI: 10.1007/s12204-022-2562-y Abstract （89）      PDF（pc） （2362KB）（36）       Knowledge map    Save The dynamics of negative surface discharges in c-C4F8/CF3I/CO2 gas mixture is investigated here with a 2D fluid model. The distributions of ion concentration, electric field strength and photon flux during the propagation of the streamer are obtained by solving the drift-diffusion equations of particles and Poisson’s equation, and the photon flux variation function during the propagation is also fitted. It is found that the streamer branches occur when the streamer transitions from the upper surface of the insulator to the side surface, and then when the streamer approaches the plane electrode, the photon flux will increase significantly. On this basis, the positive and negative surface discharge models are compared in terms of streamer characteristics, particle characteristics and streamer branches. It is found that the streamer has a higher electron concentration and electric field in the positive model. The streamer develops “floating” in the positive surface discharge, while it is close to the surface of the insulator in the negative model. In addition, the negative streamer branch has a wider width and develops further. Reference | Related Articles | Metrics | Comments（0）

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Fast Four-Stage Local Motion Planning Method for Mobile Robot HUANG Shan(黄山), HUANG Hongzhong(黄洪钟), ZENG Qi(曾奇) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 428-435.   DOI: 10.1007/s12204-022-2423-8 Abstract （130）      PDF（pc） （1810KB）（35）       Knowledge map    Save Mobile robot local motion planning is responsible for the fast and smooth obstacle avoidance, which is one of the main indicators for evaluating mobile robots’ navigation capabilities. Current methods formulate local motion planning as a unified problem; therefore it cannot satisfy the real-time requirement on the platform with limited computing ability. In order to solve this problem, this paper proposes a fast local motion planning method that can reach a planning frequency of 500 Hz on a low-cost CPU. The proposed method decouples the local motion planning as the front-end path searching and the back-end optimization. The front-end is composed of the environment topology analysis and graph searching. The back-end includes dynamically feasible trajectory generation and optimal trajectory selection. Different from the popular methods, the proposed method decomposes the local motion planning into four sub-modules, each of which aims to solve one problem. Combining four submodules, the proposed method can obtain the complete local motion planning algorithm which can fast generate a smooth and collision-free trajectory. The experimental results demonstrate that the proposed method has the ability to obtain the smooth, dynamically feasible and collision-free trajectory and the speed of the planning is fast. Reference | Related Articles | Metrics | Comments（0）

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Numerical Study on Effect of Suction Slot Geometric Parameters on Airflow Field in Compact Spinning LIN Huiting1,2 (杨娜), WANG Jun1∗ (张淑霞), ZHANG Yongfa3 (白牡丹) J Shanghai Jiaotong Univ Sci    2024, 29 (2): 245-251.   DOI: 10.1007/s12204-022-2521-7 Abstract （109）      PDF（pc） （1054KB）（33）       Knowledge map    Save The airflow field in the condensing zone is crucial as it affects the fiber condensing, additional twists, and consequently yarn properties. Parameters of spinning and suction slot geometric were found to be key factors influencing the airflow characteristics. To develop a better understanding of the complex airflow field within the pneumatic compact spinning system with lattice apron, a 3D numerical simulation model was built and the influence of negative pressure and geometric of suction slot was investigated. The results reveal that the accelerating air from the top of the suction slot generates transverse condensing force and downward pressure on the fiber strand. The inclination angle has a small effect on airflow velocity. The absolute z-velocity and x-velocity in the positive x-axis were both increased with increasing the slot width from 1.0 mm to 1.5 mm. An arc suction slot increased the absolute z-velocity and x-velocity compared with a linear one, thus benefiting fiber condensing. By decreasing the outlet negative pressure to −3 kPa, the airflow velocity increased significantly. Reference | Related Articles | Metrics | Comments（0）

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AlgoTime-Varying Formation-Containment Tracking Control for Unmanned Aerial Vehicle Swarm Systems with Switching Topologies and a Non-Cooperative Target WU Xiaojing∗(武晓晶), CAO Tongyao (曹童瑶), ZHEN Ran (甄然), LI Zhijie (李志杰) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 689-701.   DOI: 10.1007/s12204-024-2728-x Abstract （106）      PDF（pc） （1627KB）（33）       Knowledge map    Save This paper studies the time-varying formation-containment tracking control problems for unmanned aerial vehicle (UAV) swarm systems with switching topologies and a non-cooperative target, where the UAV swarm systems consist of one tracking-leader, several formation-leaders, and followers. The formation-leaders are required to accomplish a predefined time-varying formation and track the desired trajectory of the tracking-leader, and the states of the followers should converge to the convex hull spanned by those of the formation-leaders. First, a formation-containment tracking protocol is proposed with the neighboring relative information, and the feasibilit condition for formation-containment tracking and the algebraic Riccati equation are given. Then, the stability of the control system with the designed control protocol is proved by constructing a reasonable Lyapunov function. Finally, the simulation examples are applied to verify the effectiveness of the theoretical results. The simulation results show that both the formation tracking error and the containment error are convergent, so the system can complete the formation containment tracking control well. In the actual battlefield, combat UAVs need to chase and attack hostile UAVs, but sometimes when multiple UAVs work together for military interception, formationcontainment tracking control will occur. Reference | Related Articles | Metrics | Comments（0）

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CBF-Based Distributed Model Predictive Control for Safe Formation of Autonomous Mobile Robots MU Jianbin∗ (穆建彬), YANG Haili (杨海丽), HE Defeng (何德峰) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 678-688.   DOI: 10.1007/s12204-024-2747-7 Abstract （99）      PDF（pc） （969KB）（31）       Knowledge map    Save A distributed model predictive control (DMPC) method based on robust control barrier function (RCBF) is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed environment. The first step is to analyze the safety requirements of the system during safe formation and categorize them into collision avoidance and distance connectivitymaintenance. RCBF constraints are designed based on collision avoidance and connectivity maintenance requirements, and security constraints are achieved through a combination. Then, the specified safety constraints are integrated with the objective of forming a multi-autonomous mobile robot formation. To ensure safe control, the optimization problem is integrated with the DMPC method. Finally, the RCBF-DMPC algorithm is proposed to ensure iterative feasibility and stability while meeting the constraints and expected objectives. Simulation experiments illustrate that the designed algorithm can achieve cooperative formation and ensure system security. Reference | Related Articles | Metrics | Comments（0）

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Universal Modeling Method of Electrical Impedance Response During Respiration LIU Enkang1 (刘恩康), MA Yixin1, 2∗ (马艺馨), BAI Zixuan1 (白子轩), ZHOU Xing1 (周星), ZHANG Mingzhu1 (张明珠), JIANG Zeyi1 (江泽裔) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 967-978.   DOI: 10.1007/s12204-023-2593-z Abstract （71）      PDF（pc） （1004KB）（30）       Knowledge map    Save In recent years, significant progress has been made through impedance pneumography (IP) in diagnosing pulmonary function. Since there is no need to measure inhalation and exhalation air flow through a pipeline, IP does not increase respiratory resistance and poses no risk of cross-infection, which makes it superior to existing gas flowmeter-based spirometers in clinics. However, the changes in thoracic impedance caused by pulmonary ventilation present significant individual variability. The ratio between pulmonary ventilation volume change (ΔV ) and thoracic impedance change (ΔZ), noted as kΔV/ΔZ , differs among people. IP has to be calibrated for each person by flowmeter-type spirometer before it can be used for quantitative diagnosis. This study aimed to develop a universal model for kΔV/ΔZ using individual parameters such as body height, body mass, body mass index, body fat rate, and chest circumference. The experimental procedure, the way to identify factors for multiple regression via significance analysis and the comparison among different models are presented. This paper demonstrates the possibility of establishing a universal regression model for kΔV/ΔZ , to lay the foundation for the clinical application of IP-based pulmonary function test. Reference | Related Articles | Metrics | Comments（0）

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Attitude Stabilization of Unmanned Underwater Vehicle During Payloads Release DENG Xua (邓旭), FENG Zhengpinga, b∗ (冯正平), HE Chenlua (何晨璐), CUI Zhenhuaa (崔振华) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 766-772.   DOI: 10.1007/s12204-023-2598-7 Abstract （57）      PDF（pc） （765KB）（29）       Knowledge map    Save Large unmanned underwater vehicles can carry big payloads for varied missions and it is desirable for them to possess an upright orientation during payload release. Their attitude can hardly be maintained during and after the phase of payload release. Releasing a payload from the vehicle induces uncertainties not only in rigid-body parameters, e.g, the moment of inertia tensor due to the varying distribution of the masses on board the vehicle, but also in the hydrodynamic derivatives due to the vehicle’s varying geometric profile. A nonlinear attitude stabilizer that is robust to these time-varying model uncertainties is proposed in this paper. Stability is guaranteed via Lyapunov stability theory. The simulation results verify the effectiveness of the proposed approach. Reference | Related Articles | Metrics | Comments（0）

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Distributed Cooperative Anti-Disturbance Control for High-Order MIMO Nonlinear Multi-Agent Systems JIN Feiyu (金飞宇), CHEN Longsheng∗ (陈龙胜), LI Tongshuai (李统帅), SHI Tongxin (石童昕) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 656-666.   DOI: 10.1007/s12204-023-2673-0 Abstract （67）      PDF（pc） （680KB）（28）       Knowledge map    Save To solve the synchronization and tracking problems, a cooperative control scheme is proposed for a class of higher-order multi-input and multi-output (MIMO) nonlinear multi-agent systems (MASs) subjected to uncertainties and external disturbances. First, coupled relationships among Laplace matrix, leader-following adjacency matrix and consensus error are analyzed based on undirected graph. Furthermore, nonlinear disturbance observers (NDOs) are designed to estimate compounded disturbances in MASs, and a distributed cooperative antidisturbance control protocol is proposed for high-order MIMO nonlinear MASs based on the outputs of NDOs and dynamic surface control approach. Finally, the feasibility and effectiveness of the proposed scheme are proven based on Lyapunov stability theory and simulation experiments. Reference | Related Articles | Metrics | Comments（0）