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Adaptive optimal output regulation: A parametric Lyapunov equation approach 5

Adaptive optimal output regulation: A parametric Lyapunov eq...

引用

5th International Conference on control, Robotics, and intelligent system, CCRIS 2024

作者： ul Aabidin Lodhi, Zain Jiang, Huaiyuan Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin China

ISBN: (数字)9781510685871

ISBN: (纸本)9781510685864

This article delves into a data-driven approach for solving the adaptive optimal output regulation problem in continuous-time linear systems with uncertain dynamics. Employing a class of parametric Lyapunov equations in conjunction with a nominal system model, the initial stabilizing feedback gain is determined to initiate the iterative method. Then, by utilizing a policy-iteration-based technique, we design an optimal control policy to achieve precise output tracking and disturbance rejection. The prescribed convergence characteristics of the closed-loop system directly result from the properties embedded within the solution of the parametric Lyapunov equation. The applicability and performance of the proposed method are demonstrated through a numerical example involving an input-constrained double integrator system. © 2024 SPIE.

关键词： Continuous time systems

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Indicators and Validation Methods for Swarm Situational Awareness Assessment of Uncrewed Aerial Vehicles 1

引用

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

作者： Zhang, Hang Song, Chuang Li, WeiXue Hao, Mingrui School of Software Northwestern Polytechnical University Shaanxi Xi’an710072 China Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (数字)9789819733323

ISBN: (纸本)9789819733316

Swarm situational awareness technology for uncrewed aerial vehicles (UAVs) is a core technology for mastering environmental information and gaining decision-making advantages. However, evaluation indicators and validation methods for situational awareness technology have always been lacking. This article thoroughly investigates the evaluation methods for situational awareness technology indicators both domestically and internationally. By analyzing the application scenarios of UAV group situational awareness technology, this article proposes an evaluation indicator system and mathematical simulation validation method for situational awareness technology. Finally, the design process and actual verification results of each indicator in the evaluation indicator system are explained in detail. The effectiveness of the evaluation indicator is demonstrated through simulation and comparative research, which further proves the reliability of the validation method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Decision making

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Multi-view and Multi-target Association Algorithm for Unmanned Aerial Vehicle Clusters Based on Siamese Network

Multi-view and Multi-target Association Algorithm for Unmann...

引用

International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Zhang, Hang Song, Chuang Zheng, JiangBin Hao, MingRui School of Software Northwestern Polytechnical University Shaanxi Xi’an710072 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811966125

The multi-target association algorithm of unmanned aerial vehicles (UAV) clusters in unknown environments is used to solve the problem of multiple UAVs, which can correctly determine whether the data from different perspectives contain the same target and eliminate redundant targets. This problem is different from that of multi-target tracking under the same perspective. However, the inherent relationship and differences of data from various perspectives of UAV clusters contribute to the problem of inaccurate target positioning information caused by low-cost detectors and inertial measurement units of UAVs and the constraints of limited communication capability between UAV clusters. Thus, using multi-perspective data is the key to improving the accuracy of multi-perspective situational awareness. This paper proposes a multi-view and multi-target association algorithm for UAV clusters based on the Siamese network. This algorithm can realise the problem of multi-view and multi-target identity judgement with high accuracy, achieve the requirements of high accuracy and high generalisation performance with the depth model based on convolution neural networks, extract the depth features from the optical image and map the original data to the depth feature space. Thus, the same target is matched by comparing the distance measurement of multi-view data in the feature space. The algorithm is verified by an aircraft cluster flight test, which proves the feasibility and accuracy of the algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Design of Conical Equiangular Spiral Antenna with Wide Bandwidth and High Gain 4

Design of Conical Equiangular Spiral Antenna with Wide Bandw...

引用

4th International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2021

作者： Zong, Liping Zong, Xianzheng Nie, Zaiping Wang, Youcheng Jiang, Peng School of Electronic Science and Engineering UESTC Chengdu China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (纸本)9781733509619

In this paper, an ultra-wideband conical equiangular spiral antenna has been designed. The presented antenna covers an operating bandwidth of f-{0}-10f-{0}. In the design, by loading absorbing materials, the voltage standing wave ratio (VSWR) of the antenna in the low frequency is improved, and the addition of metal cone structure increases the gain of high frequency, which makes the antenna performance improved in the whole band. © 2021 Applied Computational Electromagnetics Society (ACES).

关键词： Spiral antennas

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An initial alignment approach for improving the accuracy of azimuth setting

An initial alignment approach for improving the accuracy of ...

引用

2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Guan, Xujun Wang, Xing Guo, Jianzhong Fu, Wenxing Meng, Lingbao Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China China Aerospace Science and Industry Corporation Beijing China

ISBN: (纸本)9781728137926

Considering the azimuth discrepancy between the main and sub-inertial navigation systems (INS) for a platform-carried unmanned aerial vehicles(UAV) in case of tilted launching at a large pitch angle, an initial alignment method for improving the accuracy of the azimuth setting is proposed. First, an algorithm for computing the azimuth discrepancy is derived. Then, a mathematical model for initial alignment is established based on azimuth setting. The simulation results show that correcting the azimuth discrepancy between the main and sub-INS can greatly improve the accuracy of azimuth setting, and therefore the initial alignment accuracy of the sub-INS. Meanwhile, the drift for the gyros in three directions can be effectively estimated. © 2019 IEEE.

关键词： Inertial navigation systems

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Relative Position-Based Collaborative Navigation for Cluster UAVs 7th

Relative Position-Based Collaborative Navigation for Cluster...

引用

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

作者： Sheng, Danting Cheng, Jin Li, Fengyi Hao, Mingrui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Aerospace Science and Industry Group Intelligent Technology Research Institute Co. Ltd. Beijing100074 China

ISBN: (纸本)9789819733316

The inertial equipment carried by UAVs without satellite signal assistance will accumulate errors over time, which cannot meet the requirement of obtaining high-precision cluster navigation information for cluster UAVs in long-duration flights. Aiming at this problem, a scheme for cooperative navigation of cluster UAVs based on relative position assistance is proposed. Firstly, the state equations of the cooperative navigation system are established by modeling the errors of inertial devices of low-precision UAVs;secondly, the relative position information of low-precision UAVs and high-precision UAVs as well as other low-precision UAVs transmitted between UAVs through the data chain is taken as the observation equation;finally, the inertial errors of low-precision UAVs are compensated by using the traceless Kalman filtering for the error compensation, which improves the navigation accuracy. After 30 min simulation results show that the cooperative navigation scheme converges the velocity and position errors of the low-precision UAV to 0.5 m/s and 5 m, respectively, which improves the navigation accuracy greatly. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Unmanned aerial vehicles (UAV)

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Cross-Domain Guidance Positioning Method Based on Multi-Layer Network Structure 21

Cross-Domain Guidance Positioning Method Based on Multi-Laye...

引用

3rd European Symposium on Computer and Communications, ESCC 2021

作者： Wu, ChengFeng Guo, XiaoYun Xu, Cheng Qi, Hang Liu, Yanxu Zhao, Jianmin Hu, Enwen Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory China Beijing University of Posts and Telecommunications China

ISBN: (纸本)9781450387491

Oriented towards the requirements for reliable positioning and navigation of aircraft under the condition of rejection of navigation satellite, we proposed cross-domain guide positioning methods based on multi-layer network coverage, and designed the relative positioning network construction methods between ground nodes, aircrafts and ground nodes, aircrafts and target nodes. Combined with the relative positioning network characteristics of each layer, at the same time, considered the computational complexity and location accuracy, the self-established multi-point coordinate system method and the robust location method are proposed. © 2021 ACM.

关键词： Aircraft

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An Optimized Method of Low RCS Carrier Design 4

An Optimized Method of Low RCS Carrier Design

引用

4th International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2021

作者： Zhang, Hanfei Zong, Xianzheng Nie, Zaiping Wang, Youcheng Jiang, Peng School of Electronic Science and Engineering UESTC Chengdu China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (纸本)9781733509619

Due to the strong scattering intensity of the apex of the carrier, a scheme of rounding the apex of the carrier is proposed. In this design, it is embodied in face fillet and line fillet. Based on the above designs, this paper compares the smooth transition with the sharp transition carrier, and draws a general conclusion about the low scattering carrier design method. © 2021 Applied Computational Electromagnetics Society (ACES).

关键词： Design

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An Adversarial Defense Algorithm Based on Triplet Network and Voting Decision

An Adversarial Defense Algorithm Based on Triplet Network an...

引用

2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Zheng, Haonan Zhao, Jiajia Tan, Wei School of Electronics and Information Northwestern Polytechnical University Shaanxi Xi'an710072 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

In the field of artificial intelligence, neural network is one of the key technologies used for image classification and recognition. However, recent work has demonstrated that deep neural networks are easily attacked by adversarial examples to make misjudgments. Adversarial examples are almost indistin-guishable from normal examples and yet cannot be classified correctly by neural networks. The existence of adversarial examples is a major obstacle to the practical application and deployment of neural networks, so the research on adversarial defense algorithms is an important topic in the field of AI security. This paper proposes an adversarial example defense algorithm based on a triplet network and voting decision mechanism. Firstly, two neural networks with different structures are trained based on normal dataset. Secondly, the first network is fine-tuned using the adversarial examples generated by these two networks, resulting in a third neural network. Then, these three neural networks are used as sub-networks in parallel to construct a triplet network. Through adversarial training and differences in structures, the transferability of adversarial examples among the three sub-networks is weakened. Finally, the final classification result is obtained by majority voting, based on the parallel output results of the three sub-networks. Through the complementarity between these three sub-networks, the defense against adversarial examples is realized. The experimental results demonstrate the effectiveness of this algorithm. © 2022 IEEE.

关键词： Deep neural networks

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A Comparative Study on Adversarial Attacks for Visible and Infrared Images

A Comparative Study on Adversarial Attacks for Visible and I...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Guo, Haiwang Tan, Wei Zhao, Jiajia School of Electronics and Information Northwestern Polytechnical University Shaanxi Xi'an710072 China Agent Cooperation Laboratory Science and Technology on Complex System Control and Intelligent Beijing100074 China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

In recent years, the booming development of artificial intelligence has driven the development and progress of society. With its excellent performance, deep learning has been widely used in many fields, including some security-sensitive fields such as unmanned systems, auto-driving and so on. Research has found that deep neural networks are vulnerable to adversarial samples, which can lead to misclassification of neural networks and can cause serious safety incidents. Hence, the study of adversarial samples has received increasing attention, and researchers have conducted studies from different perspectives, and relevant research results have emerged. However, most of these studies have focused on visible images, and few have studied infrared images, which play an important role in military and other important fields. In this paper, a comparative study on adversarial attacks for visible and infrared images is presented. A number of adversarial attack experiments are conducted on ResNet18 and VGG16 models for visible and infrared images. By comparing the experimental results, the characteristics of infrared adversarial samples are derived relative to those with visible adversarial samples. Then, a gradient attack method from a frequency domain perspective is proposed. The adversarial perturbation noise is added to the low frequency component of images. It is verified experimentally that the proposed method improves the transferability of infrared adversarial samples compared to some baseline methods. © 2022 IEEE.

关键词： Deep neural networks

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