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Chinese Automation Congress (CAC)

作者： Kai Zhou Weihua Cao Chao Gan Yupeng Li 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

Troublesome incidents like sudden water inflows increase the risk of collapse accidents in tunnel excavation. In this study, a data-driven underground water prediction method is proposed based on trend features extracted from apparent resistivity. A novel framework is developed for extracting trend features from the contour lines of apparent resistivity. These trend features are subsequently integrated with numerical features from the resistivity matrix for classification. The effectiveness of the proposed method is demonstrated by apparent resistivity data from real tunnel engineering. The result indicates that the classification accuracy of the proposed method outperforms the method without feature extraction.

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An Active Suppression Method Considering Input Time-Delay for Stick-Slip Vibration in the Drilling Procedure

An Active Suppression Method Considering Input Time-Delay fo...

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Chinese Control Conference (CCC)

作者： Hao Sun Chengda Lu Zhaoqing He Shengnan Tian Zhejiaqi Ma Min Wu 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 uses the wave equation to explain the torsional motion of the drill-string system. Solving the wave equation with the D'Alembert method, a neutral time-delay model of the drill-string system is obtained. The disturbance input, caused by the bit-rock interaction, is given consideration, and an equivalent-input-disturbance (EID) based controller is designed to mitigate the disturbance in the established model. In the actual drilling procedure, the system input time-delay increases as the length of the drill columns increases. If the influence of system input time-delay in the drilling procedure is ignored, it will most likely lead to the drill-string system instability and cause serious consequences. The essential contribution of this paper is the incorporation of input time-delay into the EID based control structure. Considering the system's input time-delay, the proposed model is more practical and has significant implications for stick-slip vibration assessment and control in drilling procedures.

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Towards Time-Variant-Aware Link Prediction in Dynamic Graph Through Self-supervised Learning 9th

Towards Time-Variant-Aware Link Prediction in Dynamic Graph...

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19th International Conference on Advanced Data Mining and Applications, ADMA 2023

作者： Wen, Guangqi Cao, Peng Jin, Zhiyong Song, Ruoxian Liu, Xiaoli Yang, Jinzhu Zaiane, Osmar R. Computer Science and Engineering Northeastern University Shenyang China Key Laboratory of Intelligent Computing in Medical Image of Ministry of Education Northeastern University Shenyang China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Shenyang110819 China DAMO Academy Alibaba Group Hangzhou China Alberta Machine Intelligence Institute University of Alberta EdmontonAB Canada

ISBN: (纸本)9783031466731

Dynamic graph link prediction is a challenging problem because the graph topology and node attributes vary at different times. A purely supervised learning scheme for the dynamic graph data usually leads to poor generalization due to insufficient supervision. As a promising solution, self-supervised learning can be introduced to dynamic graph analysis tasks. However, the self-supervised learning paradigm for dynamic graph learning has not been sufficiently investigated due to the complicated properties of the evolving graphs. We assume that the dynamic graphs consist of three independent types of key factors, i.e., graph time-variant information, time-invariant information and noise. Based on this assumption, we propose the Self-supervised Decoupling for Dynamic Graph (SDDG) framework for explicitly decoupling the representation which characterizes these three factors, thus enhancing the interpretability of the learned representation and link prediction performance. More specifically, we design an encoder-decoder architecture to sufficiently exploit the dynamic graph itself with multiple regularizations, so that the time-variant embedding of dynamic graph data can be effectively decoupled from the perspectives of node and structure for time-variant-aware link prediction. Experiments on five benchmark link prediction tasks demonstrate the significant improvement of our SDDG over the state-of-the-art methods. For example, SDDG achieves 98.2% and 97.3% Top-1 AUC on Reddit-B and Reddit-T, outperforming the DDGCL model, by 1.9% and 1.8%, respectively. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Supervised learning

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HDD4DBP: A Large-Scale Multi-Modal Benchmark on Driving Behavior Prediction

HDD4DBP: A Large-Scale Multi-Modal Benchmark on Driving Beha...

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IEEE International Conference on systems, Man and Cybernetics

作者： Qinghui Dong Zhang Zhang Yubo Chang Wentao Chen Liang Wang Center for Research on Intelligent Perception and Computing State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Driving behavior prediction (DBP) plays an important role in autonomous driving. Accurately anticipating driving behaviors (e.g., left turn, right turn) of ego-vehicles 3–5 seconds before actual occurrences of maneuvers can help AI pilots planning safer trajectories or informing possible dangers to drivers. However, current DBP benchmark datasets, e.g., the Brain4Cars, are restricted by the limited amount of data samples and small number of behavior categories. Thus, there is an urgent need for creating a new larger-scale benchmark to help boost the studies of DBP. In this work, based on the annotations in the HRI Driving Dataset (HDD), we extract 5000+ clips from untrimmed multi-modal data sequences to form a new dataset, termed the HDD4DBP, as a convincing large-scale testbed for evaluating various DPB methods. Furthermore, inspired by the success of transformers on modeling long range dependence in sequences, we build a strong baseline with the vision transformer (ViT) backbone for predicting driving behaviors. Compared to previous representative baselines, a large margin performance gain can be achieved by our strong baseline on the HDD4DBP. Moreover, simply fine-tuning the pre-trained strong baseline can obtain the state-of-the-art performance on the Brain4Cars dataset, thereby futher confirming the benefits of the HDD4DBP. The dataset and source code will be released. Find data and code at https://***/HDD4DBP/MTL.

关键词： Accuracy Source coding Benchmark testing Predictive models Performance gain Transformers Trajectory Planning Driver behavior Vehicles

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Distributed Control Strategy for Layered Barrier Coverage of Multi-Agent systems in Uncertain Environments

arXiv

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arXiv 2023年

作者： Fan, Pengyang Zhai, Chao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems and Engineering Research Center of Intelligent Technology for Geo-exploration Ministry of Education Wuhan430074 China

This paper presents a distributed multi-layer ring barrier coverage algorithm. In order to achieve single-layer ring barrier coverage, a distributed single-layer ring barrier coverage algorithm that maximises the probability of monitoring is proposed. Considering the security risks of single-layer barrier coverage, a distributed adjustment mechanism between multiple layers of barriers is designed and combined with the single-layer ring barrier coverage algorithm to propose a distributed multi-layer ring barrier coverage algorithm. Furthermore, we present a theoretical analysis of the proposed algorithm to demonstrate its effectiveness and necessity. Finally, our algorithm is verified by numerical simulation and experiment. Copyright © 2023, The Authors. All rights reserved.

关键词： Multi agent systems

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Transcriptomic analysis of Andrias davidianus meat and experimental validation for exploring its bioactive components as functional foods

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Food Science and Human Wellness 2024年第1期13卷 166-172页

作者： Changge Guan Zhenglin Tan Shucheng Li Yi Wang Naoyuki Yamamoto Chong Zhang Songjun Wang Junjie Chen Xinhui Xing Key Laboratory for Industrial Biocatalysis Ministry of Education of ChinaDepartment of Chemical EngineeringTsinghua UniversityBeijing 100084China School of Life Science and Technology Tokyo Institute of TechnologyYokohama 226-0026Japan Sensing System Research Center National Institute of Advanced Industrial Science and TechnologyTsukuba 305-8565Japan Center for Synthetic and Systems Biology Tsinghua UniversityBeijing 100084China Henan Giant Salamander Protection and Development Association Luoyang 471000China Intelligent Computing Research Center Harbin Institute of TechnologyShenzhen 518071China Institute of Biopharmaceutical and Health Engineering Tsinghua Shenzhen International Graduate SchoolShenzhen 518055China Institute of Biomedical Health Technology and Engineering Shenzhen Bay LaboratoryShenzhen 518067China

Andrias davidianus(Chinese giant salamander,CGS)is the largest and oldest extant amphibian species in the world and is a source of prospective functional food in ***,the progress of functional peptides mining was slow due to lack of reference genome and protein sequence *** this study,we illustrated full-length transcriptome sequencing to interpret the proteome of CGS meat and obtain 10703 coding DNA *** functional annotation and amino acid composition analysis,we have discovered various genes related to signal transduction,and 16 genes related to *** have also found vast variety of functional peptides through protein coding sequence(CDS)analysis by comparing the data obtained with the functional peptide ***-Pro-Ile predicted by the CDS analysis was released from the CGS meat through enzymatic hydrolysis,suggesting that our approach is *** study suggested that transcriptomic analysis can be used as a reference to guide polypeptide mining in CGS meat,thereby providing a powerful mining strategy for the bioresources with unknown genomic and proteomic sequences.

关键词： Chinese giant salamander Transcriptomic analysis Bioactive components Functional peptides mining

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Distributed Leader-Following Impulsive Consensus of Nonlinear Multi-Agent systems with Partial Input Saturation

Distributed Leader-Following Impulsive Consensus of Nonlinea...

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2022 Chinese Automation Congress, CAC 2022

作者： Lan, Jiejie Jiang, Xiaowei Zhang, Xianhe You, Le School of Automation China University of Geosciences Wuhan430074 China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing400065 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China School of Electrical Engineering and Automation Hubei Normal University Huangshi435002 China

ISBN: (纸本)9781665465335

In this letter, leader-following consensus of a nonlinear MASs satisfying Lipschitz conditions with partial actuator saturation constraints is investigated First of all, an impulse control protocol which only requires local information of agents and their neighbors is proposed. Then, using Lyapunov stability theory, impulse control theory, and algebraic graph theory, sufficient conditions for the consensus of multi-agent systems are provided. Ultimately, numerical simulations are employed to show that the research findings are accurate. © 2022 IEEE.

关键词： Multi agent systems

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Constraint-Following Based Adaptive Robust Control for Underactuated Mechanical systems

Constraint-Following Based Adaptive Robust Control for Under...

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International Conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Cui Wei Ye-Hwa Chen Yanling Wei Institute of Intelligent Manufacturing Nanjing Tech University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta GA USA Key Laboratory of Measurement and Control of Complex System of Engineering School of Automation Southeast University Nanjing China

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

This paper introduces an adaptive robust control approach tailored for underactuated mechanical systems encountering matched and mismatched uncertainty, employing a constraint-following methodology. The control strategy unfolds in two phases: initially, a nominal control scheme is devised neglecting uncertainty and deviations in initial conditions from constraints. Subsequently, uncertainty is categorized into matched and mismatched components, ensuring that mismatched uncertainties remain unobservable. Leveraging the structural characteristics of the uncertainty bound, a novel segmented adaptive law is proposed and seamlessly integrated into the adaptive robust control framework. By employing the Lyapunov minimax approach, the method ensures uniform boundedness and uniform ultimate boundedness simultaneously, thereby ensuring approximate adherence to constraints for underactuated mechanical systems facing both matched and mismatched uncertainties alongside initial condition deviations.

关键词： Robust control Uncertainty Adaptive systems Costs Automation Nonlinear dynamical systems Mechanical systems Closed loop systems Robots

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MFANet: Mixed Feature Attention Network for Port Lane Detection

MFANet: Mixed Feature Attention Network for Port Lane Detect...

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Chinese Control Conference (CCC)

作者： Jinwei Zhang Jinya Su Dewei Yi Jun Yang Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education and the School of Automation Southeast University Nanjing China Department of Computing Science University of Aberdeen Aberdeen U.K.

With the advancement of industrial automation and artificial intelligence technology, unmanned port autonomy has gained increasing attention. Port automatic driving technology is a critical component of unmanned autonomous systems, enabling rubber tire gantry cranes (RTGs) to autonomously navigate by detecting port lanes and implementing control commands. In this study, a deep learning-based method is proposed for detecting port lanes in complex port scenes. The method employs the Inception module and attention mechanism to enhance lane feature extraction, and a structural loss is introduced to explicitly constrain the detection results and incorporate the prior characteristics of port lanes. A novel Mixed Feature Attention Network (MFANet) is proposed to implement the method for port lane detection. Experimental results demonstrate that MFANet effectively improves the accuracy of port lane detection while maintaining high computational efficiency. Furthermore, the performance of MFANet is evaluated in a real-world application scenario.

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Optimal Flying Location for Unmanned Aerial Vehicle Equipped with MF-RIS assisted Covert Wireless on Communication

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IEEE Transactions on Vehicular Technology 2025年

作者： Wang, Jie Li, Yunxiang Tian, Wen Dai, Yuewei Liu, Yinqiu Niyato, Dusit Nanjing University of Posts and Telecommunications School of Communications and Information Engineering Nanjing China Nanjing University of Information Science and Technology School of Electronic and Information Engineering Key Laboratory of Intelligent Support Technology In Complex Environment Ministry of Education Nanjing210044 China Nanyang Technological University College of Computing and Data Science Singapore

In the current information age, covert communication holds significant value owing to its advantages, such as heightened security, enhanced flexibility, and improved concealment, surpassing those of traditional communication methods. However, existing covert communication approaches approximate communication channel models by Line-of-Sight (LoS) links, which is insufficient due to neglecting the impact of multipath effects and applying inaccurate performance assessments. To better adapt to real-world communication channel conditions, we propose a novel covert communication model assisted by Unmanned Aerial Vehicles (UAV) equipped with Multi-Functional Reconfigurable intelligent Surface (MF-RIS), named UMCCM. Specifically, based on a mixed link of LoS and Non-Line-of-Sight (NLoS), UMCCM leverages MF-RIS as a flexible relay to enhance the signal-to-noise ratio (SNR) and effective throughput. We first derive the mixed channel model expression. Then, we transform covert constraints from incomplete gamma functions to those linked with relative entropy and accordingly optimize the UAV transmission power and block length. Finally, the optimal flying position of the UAV is obtained by analyzing the functional properties of SNR and effective throughput under these refined constraints. Extensive numerical results demonstrate the superiority of our proposed UMCCM for enhancing SNR and effective throughput over the existing works. © 2025 IEEE.

关键词： Aircraft communication

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