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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Liu, Xinyu Hao, Mingrui Fan, Yu Zhen, Yan Yue, Keyuan Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789819733279

This article provides a review of formation control for multiple aircrafts. Firstly, several commonly used aircraft formation control methods were introduced, including leader-follower approach, behavior based formation control, virtual structure method, and artificial potential field method. Considering that the controller design of these methods is mostly based on first-order differential equations and state space methods or uses fuzzy theory or neural networks, further solutions are needed in issues such as model accuracy, controller anti-interference, and controller stability analysis. Therefore, this article proposes the possibility of applying high-order fully actuated (HOFA) system theory in aircraft formation control. In response to the nonlinear, coupled, and real-time aircraft formation control problems, the development of HOFA system theory is introduced, and it is pointed out that fully actuated system (FAS) method has outstanding advantages in dealing with nonlinear, time-varying, hysteresis problems. The article summarizes the current research and practice of FAS theory in the field of single aircraft control and multi-spacecraft formation control, and then propose a new idea of designing FAS formation control method for multiple aircrafts. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Aircraft

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Review of Maneuvering Strategies in the Level Flight Section of UAV 1

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Sun, Wendi Hao, Mingrui Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing100074 China

ISBN: (数字)9789819733408

ISBN: (纸本)9789819733392

In view of the threat of the anti-missile defense system, this paper summarized the maneuver penetration strategies of the UAV in the level flight phase, in consideration of the flight ability and technological development of the aircraft. The basic ideas, advantages and disadvantages of each penetration strategy, the future development trend of mobile penetration technology and new research ideas are discussed in this paper. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Reinforcement learning

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Multi-UAV Cooperative Path-Planning under complex Threat Environment 42

Multi-UAV Cooperative Path-Planning under Complex Threat Env...

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42nd Chinese control Conference, CCC 2023

作者： Liu, Zhenchang Liu, Yuting Zhao, Hongyin Lu, Hanchen Hao, Mingrui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789887581543

This paper proposes a cooperative path-planning method based on multi-Dubins path segments to meet the penetration requirements of UAVs in a complex threat environment. A pruning strategy is used in path-planning to sift path segments, and the diversity of threat avoidance paths is considered under a reasonable calculation amount. A threat intrusion strategy is designed for no safety path condition, which makes the cooperative path-planning method have excellent robustness. A cooperative path optimization method based on particle swarm optimization is adopted for the path length and collision avoidance requirements. The simulation results show that the UAV cooperative paths can avoid the threat area under any starting and ending points, and path lengths are close to the expected length. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Unmanned aerial vehicles (UAV)

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Combat Intention Recognition of Aerial Battlefield Targets Based on LSTM 3rd

Combat Intention Recognition of Aerial Battlefield Targets B...

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3rd International Conference on Autonomous Unmanned systems, ICAUS 2023

作者： Xu, Hongfeng Zhao, Jiajia Zhang, Hang Jiang, Jixiang Chen, Linxiu Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789819710867

In the course of military operations, the battlefield situation changes rapidly, and the combat time is fleeting. How to quickly and accurately identify the enemy’s combat intention is one of the important preconditions to ensure the commander’s correct command decision and obtain the initiative in the battlefield. In this paper, aiming at the problems of low accuracy and insufficient algorithm robustness of traditional target combat intention recognition methods in air battlefield, a combat intention recognition method based on LSTM is proposed according to the characteristics of sequence and multi-dimension of target characteristic data. Based on the historical and current state characteristics, electromagnetic characteristics and action characteristics of the target obtained by the sensor, the method uses the LSTM network to build the target combat intention recognition model, and learns the changes of the target characteristics through the network model to realize the target combat intention recognition. Simulation results show that the proposed method can effectively improve the accuracy of target combat intention recognition. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Military operations

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Multi-scale Visual Feature Association Based Long-Term UAV Positioning Algorithm 1

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3rd International Conference on Autonomous Unmanned systems, ICAUS 2023

作者： Xiaozu, Li Jiajia, Zhao Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (数字)9789819710874

ISBN: (纸本)9789819710867

In order to solve the long-term drift of positioning in UAVs, we propose a multi-scale visual feature association algorithm, and applied in SLAM systems. Through the upward fusion mechanism, we fuse the image features extracted by the 30-degree angle for FOV and 120-degree angle for FOV, making full use of the ability to perceive global features in the wide FOV and the ability to perceive environmental details in the small FOV. Combined with IMU Sensors, we effectively suppress the positioning drift and improve the accuracy of the SLAM system. Using OSG to render the 3D real scene of Hong Kong, we obtain 3 trajectories in the environment including residential areas, city centers, bay highways, coastlines and mountains to test the algorithm. The experimental results show that the positioning error of the multi-scale visual feature association algorithm does not exceed 0.01% under extreme conditions such as the UAV flight trajectory length surpassing 10,000 m, sharp turn, and high speed, which proves that the algorithm in this paper can ensure the measurement accuracy of the positioning and effectively suppress drift of positioning, and has strong robustness. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Unmanned aerial vehicles (UAV)

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A Review of Target Association Methods 1

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Xu, Hongfeng Zhao, Jiajia Zhang, Hang Jiang, Jixiang Chen, Linxiu Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (数字)9789819733361

ISBN: (纸本)9789819733354

With the continuous development of information technology, target association technology has been more and more widely used in military and civilian fields. How to achieve effective and reliable target data association has always been a difficult and hot spot in the field of target tracking. In this paper, the research status of target association technology is summarized, the existing target association algorithm is sorted and summarized according to the method principle, and the existing problems in the research of target association technology are analyzed, and the further research direction is prospected. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Target tracking

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Review of Numerical Algorithms for Aircraft Trajectory Optimization 3rd

Review of Numerical Algorithms for Aircraft Trajectory Optim...

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3rd International Conference on Autonomous Unmanned systems, ICAUS 2023

作者： Jiang, Yunfei Liu, Jin Li, Fengyi Hao, Mingrui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789819711062

Flight trajectory optimization is a crucial aspect of aircraft design, and the numerical algorithms for trajectory optimization have always been a hot and challenging topic in domestic and international research. Starting from the classical classification of trajectory optimization methods and combining with recent advancements in the field of trajectory optimization, this paper provides an overview of various numerical algorithms for flight trajectory optimization, including their principles and applications. Furthermore, the characteristics of different methods and their suitability for solving specific problems are analyzed, offering valuable insights for the practical application of optimization methods. Finally, a brief analysis of the development of trajectory optimization is presented, along with a prospective outlook on the future direction of flight trajectory optimization algorithms. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Numerical methods

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Application of Generative Artificial Intelligence GPT in Unmanned Aircraft systems 1

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Liu, Xinyu Hao, Mingrui Fan, Yu Li, Fengyi Zhen, Yan Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (数字)9789819733361

ISBN: (纸本)9789819733354

This article focuses on the application of generative artificial intelligence technology in unmanned aircraft systems. In detail, it elaborates on the application scenarios of GPT in aircraft design, development and production, aircraft intelligent situational awareness, and aircraft autonomous decision-making. Then article points out the basic conditions for deploying generative artificial intelligence technology in unmanned aircrafts, such as software and hardware requirements, and large-scale databases. At the same time, this article summarizes several inspirations of the intelligent development of unmanned aircrafts and puts forward some prospects for combining generative artificial intelligence technology with aircrafts. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Decision making

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Interval analysis for neural networks with application to fault detection

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science China(Information sciences) 2024年第11期67卷 222-237页

作者： Zhenhua WANG Youdao MA Song ZHU Thach Ngoc DINH Yi SHEN Department of Control Science and Engineering Harbin Institute of Technology National Key Laboratory of Complex System Control and Intelligent Agent Cooperation School of Mathematics China University of Mining and Technology The CEDRIC-Lab Conservatoire National des Arts et Métiers (CNAM)

This paper investigates an interval analysis method for neural networks and applies it to fault detection for systems with unknown but bounded measurement noise. First, a novel interval analysis method is presented, which can compute the bounds of the output of a feedforward neural network subject to a bounded input. By applying the proposed interval analysis method to a network trained with fault-free system data, adaptive thresholds for fault detection are computed. Finally, one can acquire fault detection results via a fault detection strategy. The proposed method can achieve tight bounds of the network output and employ simple operations, which leads to accurate fault detection results and a low computational burden.A numerical simulation and an experiment on an AC servo motor are given to illustrate the effectiveness and superiority of the proposed method.

关键词： interval analysis feedforward neural network fault detection adaptive thresholds

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Infrared small target detection algorithm with complex background based on YOLO-NWD 22

Infrared small target detection algorithm with complex backg...

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4th International Conference on Image Processing and Machine Vision, IPMV 2022

作者： Zhou, Xiao Jiang, Lang Guan, Xujun Mou, Xingang Wuhan University Of Technology China Science And Technology On Complex System Control And Intelligent Agent Cooperation Laboratory China

ISBN: (纸本)9781450395823

Because of small number of occupied pixels, lacking shape and texture information, the reliability of infrared remote target detection has always been a difficult research topic. To improve the accuracy and precision of detection of infrared small targets under complex background conditions, a deep learning-based infrared small target detection algorithm YOLO-NWD is proposed. According to the characteristics of small and medium targets in infrared images, multi-channel feature fusion image was used as the input of YOLO detection framework combined with image preprocessing method. Combined with SE module and ASPP module, feature weights are explored to improve feature utilization efficiency. Finally, the normalized Wasserstein distance (NWD) loss is used to replace the original IoU calculation loss to reduce the sensitivity of small target position deviation. The experimental results show that the algorithm proposed in this paper improves the accuracy by 2.5% and the recall rate by 4%. © 2022 ACM.

关键词： Deep learning

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