检索结果-内蒙古大学图书馆

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.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Identity Re recognition technology Based on Improved Lightweight ConvNetx Model 42

Identity Re recognition Technology Based on Improved Lightwe...

引用

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

来源：评论

学校读者我要写书评

暂无评论

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

来源：评论

学校读者我要写书评

暂无评论

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

来源：评论

学校读者我要写书评

暂无评论

Prediction of Hybrid Asynchronous Frequency Hopping Pattern based on Deep Learning in Wideband Spectrum

Prediction of Hybrid Asynchronous Frequency Hopping Pattern ...

引用

2023 China Automation Congress, CAC 2023

作者： Wang, Ya Wang, Jiaqi Yuan, Shuai Liu, Naijin Lu, Yuanming Qian Xuesen Laboratory of Space Technology China Academy of Space Technology Beijing China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Unit 63893 of Pla Luoyang China

ISBN: (纸本)9798350303759

In non-cooperative scenarios, wideband frequency hopping (FH) communication reconnaissance including FH signal detection, parameter estimation, and network sorting under single-channel reception is challenging. The FH pattern contains the most information about FH signals. So it is the core of FH parameter estimation. Based on the task analysis, this paper proposes a blind prediction framework combining deep learning (DL) and clustering methods to improve the accuracy and efficiency of FH pattern estimation for mixed signals in the wideband spectrum. The unique advantage of this framework is that it requires no prior signal information and anchors but exploits the inherent time-frequency (TF) properties of asynchronous FH signals. It has a strong generalization ability and can adapt to signals of any shape. Moreover, a new comprehensive evaluation metric, normalized root mean square error including missed detection (NRMSE-MD), suitable for sequence data prediction is proposed to evaluate the level of missed detection and false detection in signal monitoring. Experimental results demonstrate the superiority of the proposed framework and the effectiveness of the proposed evaluation metric. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

UAV Typical Index Evaluation Method Based on Improving Evidence Theory

UAV Typical Index Evaluation Method Based on Improving Evide...

引用

International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Geng, Huapin Suo, Bin Tong, Jiahui Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing China Beijing Electro-Mechanical Engineering Institute Beijing China Southwest University of Science and Technology Mianyang China

ISBN: (纸本)9789811694912

It is an effective way to get more accurate results of UAV performance evaluation by fusing the data of infield test and outfield test. The common Bayes multi-source data fusion method can make comprehensive use of multiple information types while ensuring the decision risk as small as possible, but there are some risks, such as insufficient data utilization and small sample data being "submerged" by large sample data in the fusion. Due to the different scale and credibility of multi-source data, a non-uniform distribution probability sampling method is proposed based on evidence theory for the same sample space to avoid the risk of small sample data being "drowned" by large sample data;meanwhile, for the situation that the fusion weight mainly depends on the evaluation of experts is not objective enough, a comprehensive weight confirmation method of multi-source test data is proposed based on credibility measurement so as to realize the comprehensive evaluation of performance indicators based on multi-source data. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

RPViT: Vision Transformer Based on Region Proposal 2022

RPViT: Vision Transformer Based on Region Proposal

引用

5th International Conference on Image and Graphics Processing, ICIGP 2022

作者： Ge, Jing Wang, Qianxiang Tong, Jiahui Gao, Guangyu School of Computer Science and Technology Beijing Institute of Technology China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (纸本)9781450395465

Vision Transformers constantly absorb the characteristics of convolutional neural networks to solve its shortcomings in translational invariance and scale invariance. However, dividing the image by a simple grid often destroys the position and scale features in the image at the beginning of the network. In this paper, we propose a vision transformer based on region proposal, which obtains the inductive bias in a simple way. Specifically, RPViT achieves locality and scale-invariance by extracting regions with locality using a traditional region proposal algorithm and deflating objects of different scales to the same scale by a bilinear interpolation algorithm. In addition, to enable the network to fully utilize and encode diverse candidate objects, a multi-class token approach based on orthogonalization is proposed and applied. Experiments on ImageNet demonstrate that RPViT outperforms baseline converters and related work. © 2022 ACM.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

A fault isolation method using kernel canonical variate analysis-based contribution

A fault isolation method using kernel canonical variate anal...

引用

第35届中国过程控制会议

作者： Hongxin Wang Lingxia Mu Nan Feng Han Liu Ding Liu Department of Information and Control Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology School of Intelligence Science and Technology University of Science and Technology Beijing

Fault diagnosis and isolation is important for industrial system. In this paper, a kernel canonical variate analysis(KCVA) is proposed for fault isolation. KCVA is originally used as a data dimension reduction technique which can account for nonlinearity and correlations in the industrial dynamical process data. But there are some difficulties using KCVA in the construction of the contribution for the fault isolation. On the one hand, it is difficult to compute the contributions of individual variables because it is scarcely possible to find an inverse mapping from the feature space to the original space. On the other hand, a smearing effect is hardly avoided. To solve the problem, a KCVA-based contributions is proposed using the state subspace and the residual subspace which can isolate the faulty variables effectively. Simulations are conducted on the Tennessee Eastman process to verify the performance of the proposed method.

关键词： Kernel canonical variate analysis contribution plot fault isolation

来源：评论

学校读者我要写书评

暂无评论

Novel Terminal Guidance Law for Blended Aero and Reaction-Jet Missile Based on Nonlinear Disturbance Observer 1

引用

International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Zhao, Hui Xu, Cheng Qin, Hehong Wang, Hao Hu, Ying Institute of Mechanical and Electrical Engineering Beijing100072 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100072 China

ISBN: (数字)9789811694929

ISBN: (纸本)9789811694912

In this paper, an effective terminal guidance law is proposed for intercepting large maneuvering targets for the reaction jet control (RCS) missile. The guidance law takes the real dynamic characteristics of the control system into account, not only including the second order bandwidth filtering response of the autopilot, but also containing the discrete reaction jet force characteristics. For the target maneuver in the guidance loop, a new nonlinear disturbance observer (NDO) with fast convergence is presented on the premise of not obtaining the prior information of the target. Target acceleration and other uncertainties are estimated and compensated in the guidance law as a feed-forward input. Then the global stability of the system is proved by the appropriate Lyapunov function. The simulation results show that the guidance law can effectively intercept the maneuvering target and obtain good guidance precision. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Lyapunov functions

来源：评论

学校读者我要写书评

暂无评论

Decomposing Visual and Semantic Correlations for Both Fully Supervised and Few-Shot Image Classification

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1658-1668页

作者： Zhang, Chunjie Zheng, Xiaolong Beijing Jiaotong University Institute of Information Science Beijing100044 China Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China University of Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems The State of Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence Beijing100190 China

Most image classification methods are designed to either boost the classification accuracies with abundant supervision, or cope with the shortage of supervision information. This is often achieved by using the visual and semantic information of other sources. However, these methods use the visual and semantic information within the same class independently, leaving their intrinsic correlations unconsidered. Objects and disturbing components as well as noise exist on the same image. Besides, semantic representations also contain noisy information. To solve the problems mentioned above, we propose a novel method for both fully supervised image classification and few-shot image classification by decomposing visual and semantic correlations. We jointly explore the intrinsic correlations of visual and semantic information of images within the same class. For each class, we decompose its visual and semantic correlations using low-rank and sparse constraint respectively. The decomposed low-rank parts character the intrinsic correlations of images can be used in a linear transformation way. Using the decomposed parts of each class, Classification can be achieved by reconstruction error minimization. We conduct experiments on several datasets for both fully supervised image classification and few-shot image classification. Experimental results well show the effectiveness of the proposed method. © 2020 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：