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18th Chinese intelligent systems Conference, CISC 2022

作者： Diao, Guijie Gong, Ningbo Ni, Hong Liu, Zhe Tong, Jiahui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100190 China Beijing Electro-Mechanical Engineering Institute Beijing100083 China

ISBN: (纸本)9789811962257

A radio-frequency (RF) simulation method for UAV-borne imaging radar for moving ships at the sea-surface is proposed, which mainly solves the RF radar echo simulation problem for moving target at sea-surface. Based on the electromagnetic (EM) scattering model of sea-surface and ship target, the time-varying sea-surface scattering echo and moving ship target scattering echo are established respectively. Then, the scattering echo of a composite scene consisting of sea-surface background and ship-target is obtained by vector summation. Finally, the RF simulation system based on microwave anechoic chamber is constructed, and the simulation tests are carried out. Simulation results are presented to demonstrate the validity and applicability of the proposed method. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Radar imaging

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Target Recognition Inference Based on Knowledge Graph and Graph Neural Network

Target Recognition Inference Based on Knowledge Graph and Gr...

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Chinese Automation Congress (CAC)

作者： Wei Li Hongfeng Xu Yuan Li Beijing Institute of Technology Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

In complex environments with vast and diverse information sources, target recognition serves as a crucial precursor to situational analysis, providing the foundation for further decision-making and analysis. Traditional algorithms for target recognition often rely on human experience and rules, necessitating expert knowledge and subjective judgments, which introduces uncertainties. This paper introduces a method for target recognition inference, leveraging Situation Knowledge Graph Convolutional Neural Network (SKGCN). By employing active and passive radar sensor data in complex scenarios, the algorithm processes inputs within a self-constructed situational knowledge graph. It derives vector representations of target entities through aggregation operations among neighboring nodes and extracts perceptual data vectors using the embedding layer. The algorithm calculates the alignment between sensor data and target entities, facilitating target recognition and inference in complex scenarios. Simulation results confirm the effectiveness of the proposed approach.

关键词： Machine learning algorithms Target recognition Soft sensors Weapons Knowledge graphs Feature extraction Inference algorithms Vectors Data mining Convolutional neural networks

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A theoretical and deep learning hybrid model for predicting surface roughness of diamond-turned polycrystalline materials

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International Journal of Extreme Manufacturing 2023年第3期5卷 620-644页

作者： Chunlei He Jiwang Yan Shuqi Wang Shuo Zhang Guang Chen Chengzu Ren Tianjin Key Laboratory of Equipment Design and Manufacturing Technology Department of Mechanical EngineeringTianjin UniversityTianjin 30054People’s Republic of China Department of Mechanical Engineering Keio UniversityYokohama 223-8522Japan Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System School of Mechanical EngineeringTianjin University of TechnologyTianjin 300384People’s Republic of China School of Mechanical Engineering Yanshan UniversityQinhuangdao 066004People’s Republic of China

Polycrystalline materials are extensively employed in *** surface roughness significantly affects the working *** defects,particularly grain boundaries,have a great impact on the achieved surface roughness of polycrystalline ***,it is difficult to establish a purely theoretical model for surface roughness with consideration of the grain boundary effect using conventional analytical *** this work,a theoretical and deep learning hybrid model for predicting the surface roughness of diamond-turned polycrystalline materials is *** kinematic–dynamic roughness component in relation to the tool profile duplication effect,work material plastic side flow,relative vibration between the diamond tool and workpiece,etc,is theoretically *** material-defect roughness component is modeled with a cascade forward neural *** the neural network,the ratio of maximum undeformed chip thickness to cutting edge radius RT S,work material properties(misorientation angle θ_(g) and grain size d_(g)),and spindle rotation speed n s are configured as input *** material-defect roughness component is set as the output *** validate the developed model,polycrystalline copper with a gradient distribution of grains prepared by friction stir processing is machined with various processing parameters and different diamond *** with the previously developed model,obvious improvement in the prediction accuracy is observed with this hybrid prediction *** on this model,the influences of different factors on the surface roughness of polycrystalline materials are *** influencing mechanism of the misorientation angle and grain size is quantitatively *** fracture modes,including transcrystalline and intercrystalline fractures at different RTS values,are ***,optimal processing parameters are obtained with a simulated annealing *** experiments are performed with

关键词： diamond turning material-defect roughness component polycrystalline copper neural network simulated annealing algorithm

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Research on Cooperative Multi-constraint Guidance Law for Leader-Follower Multi-aircraft 21st

Research on Cooperative Multi-constraint Guidance Law for Le...

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21st Asia Simulation Conference, AsiaSim 2022

作者： Xin, Du Guijie, Diao Zhe, Liu Ningbo, Gong Beijing Electro-Mechanical Engineering Institute Beijing100074 China Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811991974

In this paper, the design and optimization of multi-aircraft cooperative guidance law with multi-constraint is studied for high-speed and large maneuvering targets. Firstly, the motion of the aircraft and the target are analyzed in the inertial coordinate system. The relative motion model and the corresponding state equation are established in a plane. Then, based on the sliding mode control method, the multi-constrained ballistic forming guidance law of the lead aircraft is designed to make it hit the target in multiple dimensions. Finally, the aircraft-to-target range and line-of-sight angle of the aircraft are selected as the state variables to be controlled, and the multi-constrained cooperative guidance law is designed for the follow aircraft. So that the motion of follow aircraft can track the lead aircraft accurately, the controlled state variables converges quickly, and hit the target at the same time until the end. The simulation results show that the leader-follower cooperative guidance law designed in this paper is effective for intercepting high-speed and large maneuvering targets. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sliding mode control

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Design and simulation of a two-stage linear inverted pendulum control system based on fuzzy LQR control

Design and simulation of a two-stage linear inverted pendulu...

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International Symposium on Autonomous systems (ISAS)

作者： Siting Peng Jun Ren Lei Li Yichao Ma Zhichao Song Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory The Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

This paper introduces in detail the origin of the development of automatic control methods, applications and current research hotspots. It also introduces some control methods commonly used in industrial and agricultural production, and expounds the current application hotspots and new advanced control methods that are developing rapidly. The background, current situation and classification of the inverted pendulum platform are introduced in detail. In the first chapter, the LQR method in modern control theory is introduced in detail. The influence of parameters is analyzed through simulink space modeling and simulation control experiment. At the same time, the real-time experiment is also done in combination with the hardware platform. In the second chapter, the fuzzy control theory in intelligent control is introduced in detail. By combining fuzzy control with LQR method, suitable LQR parameters are calculated by pole assignment. After proper adjustment, reasonable fuzzy rules are adopted and adaptive fuzzy control principle is applied to adjust the control situation in real time. Using simulink space modeling, a good simulation control effect is obtained. Finally, the summary is made.

关键词： Fuzzy control Analytical models Adaptation models Quantization (signal) Production Aerospace electronics Real-time systems

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Radar Target Selection Strategy Based on Improved Subjective Bayesian Reasoning

Radar Target Selection Strategy Based on Improved Subjective...

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Li, Wen Pei, Hucheng Qu, Guangzhou Hao, Mingrui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Electro-Mechanical Engineering Institute Beijing100074 China

ISBN: (纸本)9789811694912

In order to deal with the influence of dilution passive decoy jamming on target selection of UAV radar, and to enable UAV radar have more independent decision-making ability to acquire the naval ship correctly in an ocean battlefield scene containing single real ship and multiple passive decoys, a method which established the mathematical simulation model of jamming scene, and used the model as the fitness function to calculate the adequacy measurement parameters of subjective Bayesian reasoning through genetic optimization algorithm is proposed. This method is applied to UAV radar target selection, compared with traditional target selection methods using single target feature, this method can improve the accuracy of ship acquisition by comprehensive using multi-dimensional target features. Moreover, this method can further improve the joint acquisition accuracy by setting multiple adequacy measurement parameters for different radars, which prove that the method can achieve the purpose of improving the success rate of UAV radar against dilution passive decoy jamming. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Radar

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A Robust Multi-AGV Cooperative Path Planning Method Considering Spatiotemporal Distance 5

A Robust Multi-AGV Cooperative Path Planning Method Consider...

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5th International Conference on Computer Engineering and intelligent control, ICCEIC 2024

作者： Chen, Maolin Chen, Songhang Lian, Mingchang School of Advanced Manufacturing Fuzhou University Quanzhou China Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences Fuzhou China Fujian Provincial Key Laboratory of Intelligent Identification and Control of Complex Dynamic System Quanzhou China Fujian College University of Chinese Academy of Sciences Fuzhou China Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou China

ISBN: (纸本)9798331507992

With the widespread application of Automated Guided Vehicles (AGVs) in warehousing and logistics systems, the optimization of multi-AGV path planning has become a critical issue. Current methods primarily focus on minimizing operating time and energy consumption but often overlook spatiotemporal distances between paths, leading to frequent path conflicts and interferences in the system. This paper proposes a neural network based time window estimation model, designed to generate time windows that better align with dynamic environments. Based on this model, we introduce a collaborative multi-AGV path planning method that optimizes spatiotemporal distances between paths. Compared to the Conflict-Based Search (CBS) method, this approach significantly improves the spatiotemporal distance between AGVs during task execution, enhancing the robustness of AGV clusters while only marginally increasing time costs. © 2024 IEEE.

关键词： Automatic guided vehicles

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A Novel Attitude controller for Hypersonic Aircraft Based on FR-PI2

A Novel Attitude Controller for Hypersonic Aircraft Based on...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Fan, Jiajun Li, Tianyi Guo, Xian Hao, Mingrui Sun, Mingwei College of Artificial Intelligence Nankai University Tianjin300350 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Bejing100074 China

ISBN: (纸本)9789811581540

Due to the uncertainties and various noises of the Hypersonic Aircraft(HA), traditional method of designing attitude controllers based on accurate models faces immense challenges. To solve those proposed urgent problems effectively, in this paper, a innovative data-driven RL algorithm called FR-PI2 is proposed for the task of Hypersonic Aircraft attitude control, wherein several key techniques are introduced. Firstly, Hypersonic Aircraft attitude control is transformed into a stochastic optimal control problem, and the numerical solutions of the proposed stochastic optimal control problem are obtained with a path-integral-based method, called Policy Improvement with Path Integrals(PI2). Secondly, a model-free policy parameterization method with PID controller is integrated into the PI2 algorithm to ensure a low dependency of the Hypersonic Aircraft system model. Thirdly, a brand-new sample filtration method is proposed to guarantee rapid convergence, and an online optimization technology called rolling optimization is applied to guarantee optimality and real-time performance. Two series of experiments are carried out and analyzed to demonstrate the outstanding performance of the FR-PI2 algorithm. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

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Full Attention Tracker: A Good Combination of Pixel-Level and Region-Level Cross-Correlation 42

Full Attention Tracker: A Good Combination of Pixel-Level an...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Yuxuan Yan, Liping Feng, Zihang Xia, Yuanqing Xiao, Bo School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100081 China

ISBN: (纸本)9789887581543

The tracker based on Siamese neural network is currently a technical method with high accuracy in the tracking field. With the introduction of transformer in the visual tracking field, the attention mechanism has gradually emerged in tracking tasks. However, due to the characteristics of attention operation, Transformer usually has slow convergence speed, and its pixel-level correlation discrimination in tracking is more likely to lead to overfitting, which is not conducive to long-term tracking. A brand new framework FAT was designed, which is the improvement of MixFormer. The operation for simultaneous feature extraction and target information integration in MixFormer is retained, and the Mixing block is introduced to suppress the background as much as possible before the information interaction. In addition, a new operation is designed: the result of region-level cross-correlation is used as a guidance to help the learning of pixel-level cross-correlation in attention, thereby accelerating the model convergence speed and enhancing the model generalization. Finally, a joint loss function is designed to further improve the accuracy of the model. Experiments show that the presented tracker achieves excellent performance on five benchmark datasets. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Pixels

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An Algorithm of INS Error Correction Base on the Intermittent Label Measurement and the Analysis of Its Influencing Factors

An Algorithm of INS Error Correction Base on the Intermitten...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Peng, Siting Qian, Zhao Ma, Yichao Song, Zhichao Beijing Electro-Mechanical Engineering Institute Beijing100074 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811581540

Integrated navigation technology is widely used in aviation, aerospace, sailing and other ground-based navigation equipment, the inertial navigation system (INS) is the most common tool. In practice, the key to navigation is precise position, and the position is cooperated with the image matching. According to the label results after image matching, the position of sensor can be calculated. However, the label results cannot be get in every period, what’ more, he output results of the inertial navigation system (INS) is with big error, thus the article studied an algorithm of INS error correction based on the intermittent label measurement, in which the cubature kalman filter is used. After that, it also studied the influencing factor of the labels, such as the label error by match, the count of label, the area of label, thus the INS positioning error can be reduced in line with the engineering guarantee. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Error correction

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