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Solving Ascent Trajectory Optimization Problems by Radua Pseudospectral Method

Solving Ascent Trajectory Optimization Problems by Radua Pse...

引用

2022 International Symposium on intelligent Robotics and systems, ISoIRS 2022

作者： Deng, Liaochao Xu, Cheng You, Weishuai Beijing Institute of Mechanical and Electrical Engineering Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781665455213

Ascent trajectory optimization problem of air-breathing hypersonic vehicles is a highly nonlinear and nonconvex problems. Most of the early works focus on the traditional indirect method, which needs to derive the complete first-order necessary conditions of the trajectory optimization problem. The derivation process is too complicated and error-prone. Additionally, indirect method has a high demand on the initial guess, and it needs to give the initial guess of covariant variables without physical significance. In this paper, we solve the ascent trajectory optimization problem directly using Radau Pseudospectral Method (RPM). Firstly, the complex three-dimensional ascent trajectory optimization problem is established in detail. Conmmon inequality path constraints including those on dynamic pressure and aerodynamic bending moment are taken into account. The performance index is given as maximizing the final mass considering minimizing the fuel consumption. Subsequently, the ascent trajectory optimization problem is transformed into a nonlinear programming problem (NLP) by RPM. Finally, the ascent trajectory optimization for Generic Hypersonic Aerodynamic Model Example (GHAME) is solved by RPM and the optimal results demonstrate the rapidity, effectiveness and high precision of RPM. The comparison between optimal trajectories with and without path constraints shows that path constraints increase fuel consumption. © 2022 IEEE.

关键词： Hypersonic vehicles

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complex-Valued Signal Capsule Network for Automatic Modulation Classification

Complex-Valued Signal Capsule Network for Automatic Modulati...

引用

International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Yang, Shuyuan Feng, Zhixi Wang, Nengguo Bu, Yunong Hu, Hao Luoyang471003 China Xidian University Shannxi China Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9789811694912

Most current deep learning (DL) based AMC methods often require a large number of labeled samples to drive itself optimization study, so as to achieve a more superior performance. However, for many AMC tasks with a small amount of data, the AMC method based on deep learning still has many challenges, which makes the deep neural network model trained on a small dataset lack effective migration effect, leading to the failure to achieve better performance effect in the testing process. In this paper, we propose a novel AMC method based on complex-valued Signal Capsule Network (CSCN). Compared with other DL based methods, the proposed CSCN can achieve a better performance under the condition of small dataset and low SNR on the well-known deepsig dataset RML2016.10a and RML2016.10b. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep neural networks

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Adversarial Example Attack and Defence of Object Recognition: A Survey

Adversarial Example Attack and Defence of Object Recognition...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Tan, Wei Zhao, Jiajia Liang, Xinkai Lu, Hanchen Song, Baogang Guan, Hao Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beijing Mechano-Electronic Engineering Institute Beijing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

Deep learning-based intelligent object recognition algorithm has been widely applied in object detection, auto driving, ect. However, deep neural network is very vulnerable because of its high-dimensional linearization. The object recognition results can be easily mis-leaded through a tiny disturbance in the original image. This kind of sample that adds tiny disturbance to the original image is called adversarial example. The adversarial example attack is a factor that must be considered in the design of robust object recognition algorithm, that is, the need for adversarial defence. An in-depth understanding of adversarial attack can help the model defend successfully. In this survey, an introduction of adversarial attack and defense aiming to object recognition algorithm at the present stage is summarized, and the challenges to be faced and the development trend in the future are pointed out. © 2022 IEEE.

关键词： Object recognition

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Design of Reinforcement Learning Environment for Multiple UAV Area Coverage Search

Design of Reinforcement Learning Environment for Multiple UA...

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Sun, Yinjiang Zhang, Rui Liu, Xiaoheng Liang, Wenbao Xu, Cheng Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9789811694912

Unmanned aerial vehicle (UAV) plays an increasingly important role both in civil and military fields. As a typical mission, area coverage search is a primary measure for reconnaissance and surveillance of unknown areas. Due to the limited information about the mission area, UAV needs adaptiveness to the dynamic changes of the area and makes decisions based on local observation. It puts higher demands on the response speed of UAV, and traditional planning methods are tough to be directly applied. The problem becomes more noticeable for multiple UAV because of the heterogeneous function and large scale, and new solutions are urgently required. In this paper, the feasibility of reinforcement learning (RL) for performing area coverage search is explored, and an environment is designed for RL training and evaluation. Simulation results show that multiple UAV can cooperate and perform the mission with pretty high coverage. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Research on Location Algorithm Based on SAR and Infrared Fusion 1

引用

International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Yang, Yanjiao Qu, Guangzhou Li, Bo Ma, Meng Liu, ShuaiShuai Chi, QingXi Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Coopration Laboratory Beijing China

ISBN: (数字)9789811694929

ISBN: (纸本)9789811694912

Aiming at the problem of sins cumulative error correction, a dual-mode navigation algorithm based on infrared and SAR information fusion is studied. Radar system can provide SAR image and range information, and can measure height under certain conditions, but it cannot work in front. Infrared system can provide infrared image and optical axis direction of infrared lens. Based on the satellite positioning algorithm, this paper studies a fusion algorithm of radar SAR image and infrared. The image matching and measurement results are used to navigate to correct the accumulated errors of sins. Simulation results show the effectiveness of the algorithm. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Radar imaging

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Safe Tracker: A Robust Aerial system for Safe Tracking in Cluttered Environments 42

Safe Tracker: A Robust Aerial System for Safe Tracking in Cl...

引用

42nd Chinese control Conference, CCC 2023

作者： Hui, Yulin Tian, Bailing Zhang, Xuewei Lu, Hanchen Shen, Hongming School of Electrical and Information Engineering Tianjin University Tianjin300072 China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789887581543

This paper proposes Safe Tracker, an autonomous aerial tracking framework based on vision sensor that can deal with challenging tracking missions and guarantee safety and visibility. Firstly, a RGB-D sensor based segmentation method is employed to locate the target in real-time. Then target motion is predicted for a short time horizon, based on which a heuristic path searching method is applied to generate an occlusion-free path. Finally, particular formulations to balance visibility and safety are designed, and an effective non-linear trajectory optimization method enables to generate an optimal tracking trajectory. Autonomous aerial tracking experiments using a vision sensor are conducted to demonstrate the effectiveness of the proposed Safe Tracker in a challenging cluttered forest and a room full of sharp turns using Gazebo. Benchmark comparisons validate that our method tracks more safely and robustly than the state-of-art method. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Trajectories

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Identity Re recognition technology Based on Improved Lightweight ConvNetx Model 42

Identity Re recognition Technology Based on Improved Lightwe...

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42nd Chinese control Conference, CCC 2023

作者： Siting, Peng Lei, Li Zhu, Hongbo Jun, Ren Zhichao, Song Yang, Jiabing The Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beihang University School of Electronics and Information Engineering Beijing China

ISBN: (纸本)9789887581543

In the engineering field, there is a requirement for re recognition, including the identity recognition of cooperative and non-cooperative targets, that is, different sensors shoot targets in the same scene, and the identity recognition of targets from two perspectives is required, also known as target accurate retrieval. This method is widely used in fields such as automatic driving and military strikes. In the actual application scenario, deploying the re-recognition algorithm on the embedded processor needs to ensure the real-time computing speed and accuracy, so the complexity of the deep learning algorithm must be reduced, and pruning and lightweight processing are required. In the engineering field, when the image acquired by the sensor is subject to natural interference such as cloud and fog weather or fire and smoke, the difficulty of re-recognition increases. This paper adopts the lightweight improvement of ConvNeXt network model, and fine-tuned it on the basis of its original feature extraction function, so that it can successfully migrate to infrared image classification and also complete the extraction of infrared image target detail distinguishing features, and at the same time introduce the alignment of similar targets in infrared cross-view recognition. In the original similarity calculation, the average value is directly obtained from the spatial dimension of the output feature layer, which is replaced by the weight of the position in each space for estimation. The feature information of the multi-view marine ship target is extracted from the multi-sensor marine image, and its similarity is calculated, so as to determine the identity, thus reducing the support conditions and reconnaissance costs, and improving the accurate detection and tracking ability under the diverse dynamic reconnaissance conditions. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Feature extraction

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Tightly-Coupled Lidar-Visual-Inertial Odometry and Mapping in Real Time 42

Tightly-Coupled Lidar-Visual-Inertial Odometry and Mapping i...

引用

42nd Chinese control Conference, CCC 2023

作者： Ma, Wenyu Tian, Bailing Lu, Hanchen Shen, Hongming School of Electrical and Information Engineering Tianjin University Tianjin300072 China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789887581543

We proposed a tightly-coupled Lidar-visual-inertial odometry and mapping method, which takes advantage of measurement of Lidar, visual and inertial sensors to achieve highly accurate, real-time 6DoF state estimation and map-building in GNSS-denied environments. The proposed odometry is a tightly-coupled optimization-based method, obtains robust and low drift odometry by fusing pre-integrated IMU measurements, visual features from the image, and geometric features from Lidar data. Further, we adapt an online method to mitigate degeneracy in optimization problems to improve robustness in environmentally degenerate cases. Simulation and real-world experiments show that the proposed method exhibits similar or better robustness and accuracy with the state-of-the-art SLAM methods. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Optical radar

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Static Unstable STT Overload control on High-order Fully Actuated system Theory

Static Unstable STT Overload Control on High-order Fully Act...

引用

International Symposium on Autonomous systems (ISAS)

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

This article proposes a joint overload controller for pitch and yaw channels on the high-order fully actuated system theory for a nonlinear lateral and longitudinal static unstable STT aircraft model. Firstly, a second-order fully actuated system model for aircraft overload was derived, and an optimal control method for lateral and longitudinal overload was designed. Through mathematical simulation verification of this controller and traditional PID controller, it is shown that the PID control method has significant shortcomings in nonlinear aircraft with coupling. However, high-order fully actuated system theory control method can better adapt to nonlinear and static instability problems, achieve stable tracking of aircraft overload commands, and have better rapidity.

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Event Trigger Mechanism-Based Robust control for Cyber-Physical systems under DoS Attack

Event Trigger Mechanism-Based Robust Control for Cyber-Physi...

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2022 Chinese Automation Congress, CAC 2022

作者： Tian, Peng Xu, Huiling Zhao, Jiajia Dong, Lewei Nanjing University of Science and Technology School of Mathematics and Statistics Nanjing210094 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100000 China

ISBN: (纸本)9781665465335

In this paper, the event trigger mechanism-based robust control problem is investigated for cyber-physical systems under denial of service attacks and disturbances. The effects of DoS attacks are regarded as a type of data packet loss. An event trigger mechanism is introduced into the control scheme design to effectively compensate the packet loss data. The robust attenuation technology is composited into control scheme to reduce the impact of disterbances. Then, by modeling the cyber-physical systems under denial of service(DoS) attack as a class of bounded sequential switching system, and constructing the corresponding Lyapunov function, the stability of the system is verified and analyzed. Finally, simulation experiments are given to verify the correctness of the above theoretical results. © 2022 IEEE.

关键词： Sequential switching

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