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第43届中国控制会议

作者： Xiaolin Qin Lei Cheng Xiang Tao Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology School of Information Science and Engineering Wuhan University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Accurately and promptly identifying harmful gases in the environment can effectively prevent many accidents. Most existing pattern recognition methods are focused on addressing gas classification problems in static scenarios, but the real world is a dynamic and changing environment. Therefore, researching gas classification in continuous learning scenarios will better meet the needs of suddenly emerging gas classification tasks in real-world environments. To address this issue, an incremental learning model was introduced into gas classification, and an improved deep convolutional network was proposed for gas image feature extraction. The proposed model and other baseline methods experimented on an open-source gas dataset. The proposed model reduces knowledge loss due to catastrophic forgetting and effectively classifies the 10 gas samples in the dataset in continuous learning scenarios compared to non-incremental methods. It outperforms other baseline incremental methods by optimizing the network's shortcut connections, making the feature extraction network easier to train and improving gas classification performance. In dynamic learning scenarios, the proposed model achieved a classification accuracy of 86.30% for 10 gas *** experimental results demonstrate that the proposed method effectively mitigates catastrophic forgetting interference and completes gas classification tasks in continuous learning scenarios.

关键词： Gas classification Incremental learning Shortcut connection Catastrophic forgetting

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Gas Source Localization for UAV Using Infotaxis-Based Three-Dimensional Algorithm and Particle Filtering

Gas Source Localization for UAV Using Infotaxis-Based Three-...

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第43届中国控制会议

作者： Duan He Cheng Lei Wang Rong Zhang Yu Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology School of Information Science and Engineering Wuhan University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Unmanned aerial vehicles(UAVs) are extensively utilized in gas source localization tasks due to their payload capacity and maneuverability. This paper presents a UAV gas source localization algorithm that utilizes three-dimensional Infotaxis and particle filter. The algorithm is designed for gas source localization of UAVs in dynamic outdoor airflow *** source localization process comprises UAV search area partitioning, particle filter initialization, observation and update of probability map, entropy calculation and direction selection, particle direction and weight update, and UAV movement. To validate the effectiveness of the algorithm, we build a CFD gas environment and UAV source localization platform, and compare it with traditional Infotaxis-based source localization algorithms. The proposed algorithm based on three-dimensional Infotaxis and particle filter demonstrates higher accuracy.

关键词： infotaxis particle filtering gas source localization olfactory drone path planning

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Collective Entity Alignment for Knowledge Fusion of Power Grid Dispatching Knowledge Graphs

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IEEE/CAA Journal of Automatica Sinica 2022年第11期9卷 1990-2004页

作者： Linyao Yang Chen Lv Xiao Wang Ji Qiao Weiping Ding Jun Zhang Fei-Yue Wang the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China the China Electric Power Research Institute Beijing 100192China IEEE the Qingdao Academy of Intelligent Industries Qingdao 256200China the School of Information Science and Technology Nantong UniversityNantong 226019China the School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China

Knowledge graphs(KGs)have been widely accepted as powerful tools for modeling the complex relationships between concepts and developing knowledge-based *** recent years,researchers in the field of power systems have explored KGs to develop intelligent dispatching systems for increasingly large power *** multiple power grid dispatching knowledge graphs(PDKGs)constructed by different agencies,the knowledge fusion of different PDKGs is useful for providing more accurate decision *** achieve this,entity alignment that aims at connecting different KGs by identifying equivalent entities is a critical *** entity alignment methods cannot integrate useful structural,attribute,and relational information while calculating entities’similarities and are prone to making many-to-one alignments,thus can hardly achieve the best *** address these issues,this paper proposes a collective entity alignment model that integrates three kinds of available information and makes collective counterpart *** model proposes a novel knowledge graph attention network(KGAT)to learn the embeddings of entities and relations explicitly and calculates entities’similarities by adaptively incorporating the structural,attribute,and relational ***,we formulate the counterpart assignment task as an integer programming(IP)problem to obtain one-to-one *** not only conduct experiments on a pair of PDKGs but also evaluate o ur model on three commonly used cross-lingual *** comparisons indicate that our model outperforms other methods and provides an effective tool for the knowledge fusion of PDKGs.

关键词： Entity alignment integer programming(IP) knowledge fusion knowledge graph embedding power dispatch

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Barrier Analysis of the Two-Deadline Game

Barrier Analysis of the Two-Deadline Game

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2023 China automation Congress, CAC 2023

作者： Xu, Ningsheng Huang, Weiwen Liang, Li Deng, Fang School of Automation Beijing Institute of Technology Beijing100081 China National Key Lab of Autonomous Intelligent Unmanned Systems Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China School of Mathematics and Statistics Beijing Institute of Technology Beijing100081 China College of Information Science and Technology Beijing University of Chemical Technology Beijing100029 China

ISBN: (纸本)9798350303759

This paper presents an in-depth study on the dead-line differential game, which is a fundamental type within qualitative differential games. Challenges exist in the research, primarily due to the complexity of the Retrograde Path Equations (RPEs) in the two-deadline game, often preventing the determination of the barrier's analytical form. To address this problem, we introduce a novel method using decomposition. We decompose the entire game into two subgames, apply Isaacs's approach to construct the barriers for each subgame individually, and then obtain the complete barrier of the entire game. In the two-dimensional space, this paper discusses the variations in the barriers and capture regions as the distance between the pursuer's position and the positions of the two deadlines changes. We have validated the methods and conclusions through a series of examples, demonstrating their effectiveness. This research offers new insights into the theoretical study of deadline games, providing more strategic choices for decision-makers in practical applications. © 2023 IEEE.

关键词： Decision making

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Mdbfusion: A Visible And Infrared Image Fusion Framework Capable For Motion Deblurring

Mdbfusion: A Visible And Infrared Image Fusion Framework Cap...

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IEEE International Conference on Image Processing

作者： Jun Chen Wei Yu Xin Tian Jun Huang Jiayi Ma School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Electronic Information School Wuhan University Wuhan China

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

As a vital technology in the field of image processing, numerous visible and infrared fusion methods have emerged with the aim of generating a single image containing salient targets and abundant details. However, owing to the influence of target motion or camera shake, source images may suffer from motion blur, resulting in blurred edges and unrecognizable objects. To address this issue, this paper bridges the gap between deblurring and fusion tasks and proposes a joint motion deblurring and fusion network for visible and infrared image (MDbFusion). On the one hand, we innovatively merge motion deblurring task into network design, which effectively ensures the capacity of MDbFusion to process images in the extreme condition. On the other hand, an Adaptive Weight Module (AWM) is designed to calculate contribution between visible and infrared features, which solves the channel contrast between two tasks, greatly reducing the complexity of network. Extensive experiments demonstrate that the MDb-Fusion outperforms state-of-the-art (SOTA) fusion algorithms in terms of preserving texture details and quantitative metrics. Furthermore, we also compare with a two-step fusion strategy that first deblurring then fusion, both with SOTA methods. The results reveal superiority of our framework in coupling and reciprocity between two tasks.

关键词： Measurement Couplings Adaptive systems Image edge detection Cameras Complexity theory Decoding

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Seismic impedance inversion based on cycle-consistent generative adversarial network

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Petroleum Science 2022年第1期19卷 147-161页

作者： Yu-Qing Wang Qi Wang Wen-Kai Lu Qiang Ge Xin-Fei Yan The Institute for Artificial Intelligence Tsinghua University(THUAI)Beijing100084China State Key Laboratory of Intelligent Technology and Systems Tsinghua UniversityBeijing100084China Beijing National Research Center for Information Science and Technology(BNRist) Tsinghua UniversityBeijing100084China The Department of Automation Tsinghua UniversityBeijing100084China The Research Institute of Petroleum Exploration and Development China National Petroleum Corporation(CNPC)Beijing100083China

Deep learning has achieved great success in a variety of research fields and industrial ***,when applied to seismic inversion,the shortage of labeled data severely influences the performance of deep learning-based *** order to tackle this problem,we propose a novel seismic impedance inversion method based on a cycle-consistent generative adversarial network(Cycle-GAN).The proposed Cycle-GAN model includes two generative subnets and two discriminative *** kinds of loss,including cycle-consistent loss,adversarial loss,and estimation loss,are adopted to guide the training *** from the proposed structure,the information contained in unlabeled data can be extracted,and adversarial learning further guarantees that the prediction results share similar distributions with the real ***,a neural network visualization method is adopted to show that the proposed CNN model can learn more distinguishable features than the conventional CNN *** robustness experiments on synthetic data sets show that the proposed method can achieve better performances than other methods in most *** the blind-well experiments on real seismic profiles show that the predicted impedance curve of the proposed method maintains a better correlation with the true impedance curve.

关键词： Seismic inversion Cycle GAN Deep learning Semi-supervised learning Neural network visualization

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Lookup table meets local laplacian filter: pyramid reconstruction network for tone mapping 23

Lookup table meets local laplacian filter: pyramid reconstru...

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Proceedings of the 37th International Conference on Neural information Processing systems

作者： Feng Zhang Ming Tian Zhiqiang Li Bin Xu Qingbo Lu Changxin Gao Nong Sang National Key Laboratory of Multispectral Information Intelligent Processing Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology DJI Technology Co. Ltd National Key Laboratory of Multispectral Information Intelligent Processing Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology and Hubei Key Laboratory of Brain-inspired Intelligent Systems

Tone mapping aims to convert high dynamic range (HDR) images to low dynamic range (LDR) representations, a critical task in the camera imaging pipeline. In recent years, 3-Dimensional Look-Up Table (3D LUT) based methods have gained attention due to their ability to strike a favorable balance between enhancement performance and computational efficiency. However, these methods often fail to deliver satisfactory results in local areas since the look-up table is a global operator for tone mapping, which works based on pixel values and fails to incorporate crucial local information. To this end, this paper aims to address this issue by exploring a novel strategy that integrates global and local operators by utilizing closed-form Laplacian pyramid decomposition and reconstruction. Specifically, we employ image-adaptive 3D LUTs to manipulate the tone in the low-frequency image by leveraging the specific characteristics of the frequency information. Furthermore, we utilize local Laplacian filters to refine the edge details in the high-frequency components in an adaptive manner. Local Laplacian filters are widely used to preserve edge details in photographs, but their conventional usage involves manual tuning and fixed implementation within camera imaging pipelines or photo editing tools. We propose to learn parameter value maps progressively for local Laplacian filters from annotated data using a lightweight network. Our model achieves simultaneous global tone manipulation and local edge detail preservation in an end-to-end manner. Extensive experimental results on two benchmark datasets demonstrate that the proposed method performs favorably against state-of-the-art methods.

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Formulation of Optimization Problems with Radiation Field Phases as Design Variables for Pattern Synthesis of Linear Antenna Arrays

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China Communications 2022年第12期19卷 86-100页

作者： Fei Zhao Jun He Sanyou Zeng Changhe Li Qinghui Xu Zhigao Zeng School of Mechanical Engineering and Electronic Information China University of GeosciencesWuhan 430074China Science and Technology on Blind Signal Processing Laboratory Southwest Electronics and Telecommunication Technology Research InstituteChengdu 610041China School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China College of Computer Hunan University of TechnologyZhuzhou CityHunan Province412007China

Pattern synthesise of antenna arrays is usually complicated optimization problems,while evolutionary algorithms(EAs)are promising in solving these *** paper does not propose a new EA,but does construct a new form of optimization *** new optimization formulation has two differences from the common *** is the objective function is the field error between the desired and the designed,not the usual amplitude error between the desired and the *** difference is beneficial to decrease complexity in some *** second difference is that the design variables are changed as phases of desired radiation field within shaped-region,instead of excitation *** difference leads to the reduction of the number of design variables.A series of synthesis experiments including equally and unequally spaced linear arrays with different pattern shape requirements are applied,and the effectiveness and advantages of the proposed new optimization problems are *** results show that the proposing a new optimization formulation with less complexity is as significant as proposing a new algorithm.

关键词： pattern synthesis evolutionary algorithms linear antenna arrays

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Oscillation Trajectory Optimization and Control Method for Two-Link Underactuated Manipulators 42

Oscillation Trajectory Optimization and Control Method for T...

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42nd Chinese Control Conference, CCC 2023

作者： Wang, Lejun Wang, Huiming Tang, Xianlun Huang, Zixin Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Wuhan430200 China School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan430205 China

ISBN: (纸本)9789887581543

This paper provides an oscillation trajectory optimization and control method for two-link underactuated manipulators (UMs) in a vertical plane. The proposed method solves the problem that the UMs cannot always enter the balance region in the partitioning method. First, we establish the system dynamic model, and analyze the system couple characteristics. Then, we program an oscillation trajectory for the active link, and use the intelligent method to obtain the trajectory parameters, so ensuring the system can reach the area adjacent to the target position through tracking control. Next, we design the controller to realize the stable control at the target position. Finally, the simulation results show the effectiveness and generality of the control strategy. © 2023 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Trajectories

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An Approach to the Construction of High-Quality Position Force Control systems for Autonomous Underwater Vehicles with a Multi-Link Manipulator

An Approach to the Construction of High-Quality Position For...

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2023 International Conference on Ocean Studies, ICOS 2023

作者： Timoshenko, Aleksandr Zuev, Aleksandr Filaretov, Vladimir Institute of Marine Technology Problems Feb Ras Institute of the World Ocean Far Eastern Federal University Laboratory of Intelligent Information Sustems for Marine Robots M.D. Ageev Vladivostok Russia Institute of Marine Technology Problems Feb Ras Laboratory of Intelligent Information Sustems for Marine Robots M.D. Ageev Vladivostok Russia Institute of Automation and Control Processes Feb Ras Sevastopol State University Laboratory of Robotic Systems Vladivostok Russia

ISBN: (纸本)9798350382457

In this paper, a new approach is proposed to the construction of control systems for autonomous underwater vehicles equipped with multi-link manipulators for high-precision execution of various technological operations on underwater infrastructure objects, including those requiring force action on these objects, in fully automatic mode. The approach is based on creating a force effect on the work object using the thrusters of the underwater vehicle. In this case, all mutual influences from the manipulator moving in a viscous water space are taken into account, including nominal mutual influences between its links, the action of the added masses and moments of inertia of the liquid, as well as viscous friction. At the same time, the values of the added masses and moments of inertia of the liquid are proposed to be identified before the start of any technological operations using sliding mode observers and identification methods based on Kalman filters. Sliding mode observers allow us to estimate the values of generalized external torques acting in each actuator of the manipulator, as well as the values of rotational velocities and accelerations of their output shafts. The resulting minor displacements of the underwater vehicle during the execution of technological operations, due to errors in determining the force effect on the body of the vehicle from the operating manipulator, are compensated with the help of onboard stabilization systems of the underwater vehicle. © 2023 IEEE.

关键词： Manipulators

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