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第43届中国控制会议

作者： Haolong Feng Songtai Wu Shengyang Liu Ting Song Fei Han Shanghai Aerospace Control Technology Institute Shanghai Key Laboratory of Aerospace Intelligent Control Technology Northwestern Polytechnical University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

As lunar missions become increasingly complex, the mission terrain will vary depending on different operating *** the future, there may be multiple lunar rovers working together, a more flexible and efficient algorithm to generate mission paths for lunar rover clusters is required. To address the path planning problem of lunar rover groups in large-scale and complex lunar terrain, this paper constructs a gridded map based on lunar image information and the actual lunar surface image is woven into a ring map. Path planning algorithms are modeled on this map, and the actual paths are projected onto the original lunar surface and into missions for implementing multi-lunar rover path planning tasks based on the conflict based search(CBS)algorithm. As the key to CBS algorithm is to resolve conflicts among agents, this paper combines the Deep Q Network with the CBS algorithm to propose a CBS algorithm based on a DQN conflict choice strategy to solve the multi-agent path planning problem for lunar rover clusters. The DQN can learn the policy of an agent, enabling it to better select paths. By integrating DQN with the CBS algorithm, path planning can become more intelligent and efficient. Finally, the simulation verifies that the CBS algorithm can effectively solve the multi-agent path planning problem and the improved CBS algorithm proposed has a certain degree of improvement in terms of solution efficiency.

关键词： lunar robots swarm multi-agent systems path planning CBS algorithm

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Prediction of Multi-Converter Gas Holders Level in Steel Enterprises based on Mechanism and Data 43

Prediction of Multi-Converter Gas Holders Level in Steel Ent...

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43rd Chinese control Conference, CCC 2024

作者： Yan, Yaliang Chen, Long Zhao, Jun Wang, Wei Dalian University of Technology School of Control Science and Engineering Dalian116024 China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education Dalian116024 China

ISBN: (纸本)9789887581581

Linz Donawitz converter gas (LDG) is an important secondary energy source in iron and steel enterprises. The accurate prediction of converter gas holder level is of great significance for the optimal scheduling of the LDG systems. Considering that there are multi-operating conditions caused by the affection of different gas holders from each other in a multiple gas holders system, this paper proposes a mechanism and data-based converter gas holder level prediction method, in which via physical mechanism analysis the operating conditions as well as their switching logics are built according to different pressures in each gas holder and valve states. Then, the least squares support vector machine (LSSVM) is employed to establish gas holders level prediction models for each operating condition. The actual operation data in an iron and steel plant of China are employed for simulation experiments. The results show that the proposed method not only can effectively identify the operating conditions of dual gas holders system, but also can achieve higher prediction accuracies compared to those of other prediction methods, providing effective guidance for the scheduling of the LDG systems. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Iron and steel plants

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Predefined-Time Distributed Fault-Tolerant control for Nonlinear Multiagent Systems Suffering From Nonaffine Faults

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3300-3311页

作者： Cheng, Shuai Xin, Bin Chen, Jie Deng, Fang Qingdao University School of Automation Qingdao266071 China Beijing Institute of Technology School of Automation Beijing100081 China Beijing Institute of Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing100081 China Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Department of Control Science and Engineering Shanghai200092 China

This article investigates the distributed predefined-time (PT) fault-tolerant control for nonlinear multiagent systems (NNMSs) with nonaffine faults. A novel distributed PT control scheme is proposed based on a new PT theorem. The switching functions are introduced into distributed control signals to avoid the singularity problem. The second-order filter technology is designed to solve "explosion of complexity" issues. The newly designed PT compensation signals are utilized to eliminate filter errors. The proposed distributed PT controller based on local information can guarantee that all signals of the closed-loop system are PT bounded, and consensus errors of NNMSs can be enforced to a small region around the origin within a predefined time. Compared with the finite/fixed time, the predefined time is an exact value given in advance, which remains constant regardless of initial states and control parameters. Finally, two comparative simulations are provided to demonstrate the presented strategy. © 2013 IEEE.

关键词： Adaptive control systems

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A Semantic Interpretation Method for Deep Neural Networks Based on Knowledge Graphs

A Semantic Interpretation Method for Deep Neural Networks Ba...

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2022 Chinese Automation Congress, CAC 2022

作者： Liu, Jingjing Xu, Song Wang, Lina Beijing Aerospace Control Institute National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing China

ISBN: (纸本)9781665465335

Despite the great success of deep neural networks in many fields, the lack of interpretability has severely limited their wide application in security-sensitive tasks. Although current interpretable methods of deep neural networks such as visualization, class activation mapping, and sensitivity analysis can help users intuitively understand the inner working mechanism of the neural networks to some extent, they are either too coarse in explanation or too complex in explanation form to read easily. In order to use semantic information which is more understandable and close to human thought to interpret the deep neural network and increase the readability of the interpretation,we propose a semantic interpretation method of deep neural network based on knowledge graph. The method takes the VGG16 network as an example, and by mining the key neuronsof the neural network, construct semantic dictionaries and knowledge maps of key neurons, and automatically generate human-understandable semantic explanatory statements based on the knowledge maps. The method provides a new idea to improve the transparency of the operation process of deep neural networks, and also provides a clearer reference basis for pruning and tuning of deep neural networks. © 2022 IEEE.

关键词： Deep neural networks

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Image Matching Method for SAR and Optical Image Based on Siamese Network 1

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3rd International Conference on Autonomous Unmanned Systems, ICAUS 2023

作者： Yang, Yanjiao Wang, Ziwei Qu, Guangzhou Ma, Meng Liu, Shuaishuai Chi, Qingxi Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9789819710874

ISBN: (纸本)9789819710867

Aiming at the difficulty of the similarity extraction between the SAR and optical satellite image, an image Matching method for SAR and Optical image based on siamese network is studied. The radar system can provide SAR images while also providing SAR distance and other measurement information. Optical satellites can obtain real-time optical images and provide corresponding longitude and latitude information. Based on the satellite positioning algorithm, the cumulative error of sins can be corrected by kalman filter using SAR and optical image matching results and SAR measurements. Simulation results show the effectiveness of the algorithm. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Synthetic aperture radar

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Brain-Inspired Object Domain Adaptive Segmentation 14th

Brain-Inspired Object Domain Adaptive Segmentation

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14th International Conference on Brain Inspired Cognitive Systems, BICS 2024

作者： Pang, Mengyin Xu, Song Wang, Lina Liu, Zhenfei Sun, Meijun Wang, Zheng College of Intelligence and Computing Tianjin University Tianjin China Tianjin Key Laboratory of Machine Learning Tianjin University Tianjin China National Laboratory of Aerospace Intelligent Control Technology Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (纸本)9789819628841

Addressing the domain shift challenge between datasets is critical to maintaining model performance. However, existing methods rarely consider the behavior of the human brain when dealing with the domain shift, resulting in poor model segmentation results. Brain-inspired strategies can enhance the migration ability and generalization performance of deep learning models across different data sets by simulating the mechanisms of the human brain in processing complex visual information. Inspired by this, we propose a Brain-inspired Domain Adaptation Network (BDANet) to solve the domain shift problem. Specifically, we adopt the teacher-student architecture for mutual learning and adversarial learning. Both the teacher and student models contain a dual-branch encoder and a brain-inspired decoder for object segmentation. Inspired by the cognitive process of the human brain, we propose a brain-inspired fusion module in the dual-branch encoder to effectively fuse the dual-branch features to obtain complete object information. In the brain-inspired decoder, we propose a brain-inspired refinement module to gradually refine the initial segmentation result and accurately segment the edges of objects. Extensive experiments demonstrate that the proposed method significantly outperforms the existing competitors on the challenging benchmark dataset under evaluation metrics. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Decoding

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Ground fissure development regularity and formation mechanism of shallow buried coal seam mining with Karst landform in Jiaozi coal mine: a case study

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Journal of Mountain science 2023年第10期20卷 3101-3120页

作者： ZHU Heng-zhong School of Energy and Mining Engineering Shandong University of Science and TechnologyQingdao 26659oChina State Key Laboratory of Strata Intelligent Control and Green Mining Co-Founded by Shandong Province and the Ministry of Science and Technology Shandong University of Science and TechnologyQingdao 266590China State Key Laboratory of Water Resource Protection and Utilization in Coal Mining Beijing 102209China

A comprehensive study was undertaken at Jiaozi coal mine to investigate the development regularity of ground fissures in shallow buried coal seam mining with Karst landform,shedding light on the development type,geographical distribution,dynamic development process,and failure mechanism of these ground fissures by employing field monitoring,numerical simulation,and theoretical *** findings demonstrate that ground fissure development has an obvious feature of subregion,and its geographical distribution is significantly affected by *** type,open type,and stepped type are three different categories of ground *** fissures emerge dynamically as the panel advances,and they typically develop with a distance of less than periodic weighting step distance in advance of panel advancing *** fissures present the dynamic development feature,temporary fissure has the ability of *** dynamic development process of ground fissure with closed-distance coal seam repeated mining is expounded,and the development scale is a dynamic development stage of“closure→expansion→stabilized”on the basis of the original development *** the perspective of topsoil deformation,the computation model considering two points movement vectors towards two directions of the gob and the ground surface is established,the development criterion considering the critical deformation value of topsoil is *** mechanical model of hinged structure of inclined body is proposed to clarify the ground fissure development,and the interaction between slope activity and ground fissure development is *** research results fulfill the gap of ground fissures about development regularity and formation mechanism,and can contribute to ground fissure prevention and treatment with Karst landform.

关键词： Karst landform Shallow buried coal seam Development regularity Formation mechanism Ground fissure Repeated mining

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Performance Assessment of GPT 4.0 on the Japanese Medical Licensing Examination

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当代医学科学（英文） 2024年第6期44卷 1148-1154页

作者： Hong-lin WANG Hong ZHOU Jia-yao ZHANG Yi XIE Jia-ming YANG Ming-di XUE Zi-neng YAN Wen LI Xi-bao ZHANG Yong WU Xiao-ling CHEN Peng-ran LIU Lin LU Zhe-wei YE Department of Orthopedics Surgery Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China Laboratory of Intelligent Medicine Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China Homes for the Elderly in Hainan Province Hainan 570216China Hainan Wuhua Intelligent Design and Numerical Control Technology Research Institute Hainan 571137China Laboratory of Intelligent Medicine Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China Department of Orthopedics Renmin Hospital of Wuhan UniversityWuhan 430060China

Objective:To evaluate the accuracy and parsing ability of GPT 4.0 for Japanese medical practitioner qualification examinations in a multidimensional way to investigate its response accuracy and comprehensiveness to medical ***:We evaluated the performance of the GPT 4.0 on Japanese Medical Licensing Examination(JMLE)questions(2021-2023).Questions are categorized by difficulty and type,with distinctions between general and clinical parts,as well as between single-choice(MCQ1)and multiple-choice(MCQ2)*** levels were determined on the basis of correct rates provided by the JMLE Preparatory *** accuracy and quality of the GPT 4.0 responses were analyzed via an improved Global Qualily Scale(GQS)scores,considering both the chosen options and the accompanying *** statistics and Pearson Chi-square tests were used to examine performance across exam years,question difficulty,type,and *** 4.0 ability was evaluated via the GQS,with comparisons made via the Mann-Whitney U or Kruskal-Wallis ***:The correct response rate and parsing ability of the GPT4.0 to the JMLE questions reached the qualification level(80.4％).In terms of the accuracy of the GPT4.0 response to the JMLE,we found significant differences in accuracy across both difficulty levels and option *** to the GQS scores for the GPT 4.0 responses to all the JMLE questions,the performance of the questionnaire varied according to year and choice ***:GTP4.0 performs well in providing basic support in medical education and medical research,but it also needs to input a large amount of medical-related data to train its model and improve the accuracy of its medical knowledge *** integration of ChatGPT with the medical field could open new opportunities for medicine.

关键词： large language model ChatGPT artificial intelligence Japanese medical licensing examination

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Obstacle Avoidance Trajectory Correction control Method for Hopping Movement on Small Celestial Bodies

Obstacle Avoidance Trajectory Correction Control Method for ...

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第43届中国控制会议

作者： Zhe Yang Xizhen Gao Shengying Zhu School of Aerospace Engineering Beijing Institute of Technology National Key Laboratory of Science and Technology on Space Intelligent Control

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

The surface of small celestial bodies is characterized by complex morphology and irregular gravitational *** rover faces the risk of colliding with obstacles during the hopping movement,and environmental disturbances and initial errors can lead to trajectory *** response to the issue,this paper proposes an obstacle avoidance trajectory correction control method during hopping movement of the ***,the obstacle avoidance correction potential function is *** maneuver moment is determined by setting limits on trajectory errors,obstacle warning boundaries,and potential function *** the minimization of the potential field value at the final landing point as the performance metric,the analytical solution for the maneuver velocity during obstacle avoidance correction is derived by solving the linearized dynamic ***,simulation results for hopping movement on simulated surface and a small celestial body model are presented,demonstrating the effectiveness of the method in steering the rover avoiding obstacles,correcting trajectory errors,and improving hopping accuracy.

关键词： Hopping movement Obstacle avoidance Trajectory correction Potential function

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Physics-Informed Neural Networks-Based Online Excavation Trajectory Planning for Unmanned Excavator

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Chinese Journal of Mechanical Engineering 2024年第5期37卷 332-348页

作者： Tao Fu Zhengguo Hu Tianci Zhang Qiushi Bi Xueguan Song School of Mechanical Engineering Dalian University of TechnologyDalian 116024China Beijing Tianma Intelligent Control Technology Co.Ltd. Beijing 101399China School of Vehicle and Energy Yanshan UniversityQinhuangdao 066004China School of Mechanical and Aerospace Engineering Jilin UniversityChangchun 130025China State Key Laboratory of High‑Performance Precision Manufacturing Dalian University of TechnologyDalian 116024China

As a large-scale mining excavator,the electric shovel(ES)has been extensively employed in open-pit mines for overburden removal and mineral *** the development of unmanned operations for ES,dynamic excavation trajectory planning is essential,as it directly influences operational efficiency and energy consumption by guiding the dipper during ***,conventional optimization-based methods for excavation trajectory planning typically start from scratch,resulting in a time-consuming process that fails to meet real-time *** address this challenge,we propose an innovative online trajectory planning framework based on physics-informed neural networks(PINNOTP)that utilizes advanced data-driven *** input to PINNOTP consists of onsite working conditions,including the initial state of the ES and the material surface being *** output is a smooth,polynomial-based curve that serves as the reference trajectory for the *** ensure smooth execution of the generated trajectory,prior domain knowledge-such as physics-based target-oriented constraints,essential system dynamics,and mechanical constraints-is explicitly incorporated into the loss function during training.A case study is presented to validate the proposed method,demonstrating that PINNOTP effectively addresses the challenges of online excavation trajectory planning.

关键词： Online excavation trajectory planning Physics-informed machine learning Unmanned excavator Autonomous excavation

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