检索结果-内蒙古大学图书馆

第42届中国控制会议

作者： Hairui Zhao Dongyan Chen Jun Hu School of Science Harbin University of Science and Technology Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and Technology School of Automation Harbin University of Science and Technology

In this paper,the quantized control problem is discussed for a class of highly nonlinear stochastic systems with multiple delays under the DoS *** coefficients are allowed to be highly nonlinear,and the control input is subject to the quantization effects and the DoS *** aim is to deal with the stabilization problem for unstable highly nonlinear stochastic systems with multiple *** p-th moment exponential stability and almost surely exponential stability are discussed in light of the Lyapunov ***,an illustrative example is given to verify the validity of the theoretical results.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Aerodynamic and aeroacoustic impact of the axial distance upon contra-rotating rotors during hovering condition

Aerodynamic and aeroacoustic impact of the axial distance up...

引用

AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2023

作者： Li, Pengyu Yang, Yannian Zhang, Haoyu Liu, Yu Li, Qingxi Noack, Prof. Bernd Department of Mechanics and Aerospace Engineering Southern University of Science and Technology Shenzhen Key Laboratory of Complex Aerospace Flows Guangdong Shenzhen518055 China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Unmanned Aerial Vehicle Systems Engineering Technology Research Center of Guangdong School of Automation Science and Engineering South Guangdong510640 China Department of Mechanics and Aerospace Engineering Southern University of Science and Technology Shenzhen Key Laboratory of Complex Aerospace Flows Guangdong Shenzhen518055 China AVIC General Aircraft Research Institute Zhuhai Shenzhen Key Laboratory of Complex Aerospace Flows Guangdong519040 China School of Mechanical Engineering and Automation Harbin Institute of Technology Guangdong Shenzhen518055 China

ISBN: (数字)9781624107047

ISBN: (纸本)9781624107047

Contra-rotating rotors have the advantage of compactness and redundancy, which can be observed in many unmanned aerial vehicles. One significant installation parameter for the contra-rotating rotors is the axial distance between the upper and lower rotors, which influences both the time-averaged and unsteady loading of the rotors, as well as the aeroacoustic noise emission. Through experimental methods, each rotor is mounted to a six-component balance to study the impact of the axial distance on the two rotors, and an microphone arc-array is used to study the noise emission and directivity in an anechoic chamber. Two rotors are set at the same rotational speed for all axial distance settings. The results indicate that the increase of axial distance is advantageous for the aerodynamic performance increase and noise reduction, especially in the axial range of 0.1 diameter. The recovery of aerodynamic performance is due to the fully developed slipstream which reduces the mutual influence between the two rotors. The noise reduction is mainly due to the reduced velocity fluctuation alleviates the inter actiontonal noise, although the broadband noise becomes larger as the axial distance increases. © 2023, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Noise abatement

来源：评论

学校读者我要写书评

暂无评论

Nonrigid Object Contact Estimation With Regional Unwrapping Transformer

arXiv

引用

arXiv 2023年

作者： Xie, Wei Zhao, Zimeng Li, Shiying Zuo, Binghui Wang, Yangang Southeast University China The Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

Acquiring contact patterns between hands and nonrigid objects is a common concern in the vision and robotics community. However, existing learning-based methods focus more on contact with rigid ones from monocular images. When adopting them for nonrigid contact, a major problem is that the existing contact representation is restricted by the geometry of the object. Consequently, contact neighborhoods are stored in an unordered manner and contact features are difficult to align with image cues. At the core of our approach lies a novel hand-object contact representation called RUPs (Region Unwrapping Profiles), which unwrap the roughly estimated hand-object surfaces as multiple high-resolution 2D regional profiles. The region grouping strategy is consistent with the hand kinematic bone division because they are the primitive initiators for a composite contact pattern. Based on this representation, our Regional Unwrapping Transformer (RUFormer) learns the correlation priors across regions from monocular inputs and predicts corresponding contact and deformed transformations. Our experiments demonstrate that the proposed framework can robustly estimate the deformed degrees and deformed transformations, which makes it suitable for both nonrigid and rigid contact. © 2023, CC BY-NC-SA.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Zero-Sum Differential Game-Based Fault-Tolerant Tracking control for Nonlinear systems With Multiplicative Failures

Zero-Sum Differential Game-Based Fault-Tolerant Tracking Con...

引用

2022 Chinese Automation Congress, CAC 2022

作者： Tan, Cong Lin, Mingduo Xia, Hongbing Zhao, Bo Xu, Yancai School of Systems Science Beijing Normal University Beijing100875 China Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781665465335

A novel fault-tolerant tracking control (FTTC) approach for affine nonlinear systems is developed from the perspective of zero-sum differential games (ZSDG) to deal with unknown multiplicative actuator failures in this paper. By regarding the control input and the multiplicative actuator failure as two players of a zero-sum game, a performance index function reflecting the trajectory tracking error, the control policy and the unknown failure is established. To handle the tracking Hamilton-Jacobi-Isaacs (HJI) equation associated with the established performance index function, a critic neural network is utilized. Then, the Nash equilibrium solution can be obtained, and the FTTC is achieved. The stability of the faulty nonlinear system is examined through Lyapunov-based approach. Finally, simulation results of a spring system is provided to ensure the utility and the realizability of the ZSDG-based FTTC approach. © 2022 IEEE.

关键词： Nonlinear systems

来源：评论

学校读者我要写书评

暂无评论

Cooperative Filtering with Range Measurements: A Distributed Constrained Zonotopic Method 7th

Cooperative Filtering with Range Measurements: A Distribute...

引用

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

作者： Ding, Yu Cong, Yirui Wang, Xiangke Cheng, Long College of Intelligence Science and Technology National University of Defense Technology Changsha410073 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9789819733316

This article studies the distributed estimation problem of a multi-agent system with bounded absolute and relative range measurements. Parts of the agents are with high-accuracy absolute measurements, which are considered as anchors;the other agents utilize low-accuracy absolute and relative range measurements, each derives an uncertain range that contains its true state in a distributed manner. Different from previous studies, we design a distributed algorithm to handle the range measurements based on extended constrained zonotopes, which has low computational complexity and high precision. With our proposed algorithm, agents can derive their uncertain range sequentially along the chain topology, such that agents with low-accuracy sensors can benefit from the high-accuracy absolute measurements of anchors and improve the estimation performance. Simulation results indicate the effectiveness of our algorithm and verify our method can significantly improve the estimation accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multi agent systems

来源：评论

学校读者我要写书评

暂无评论

Fast Depth Estimation of Object via Neural Network Perspective Projection 11

Fast Depth Estimation of Object via Neural Network Perspecti...

引用

11th IEEE Data Driven control and Learning systems Conference, DDCLS 2022

作者： Han, Yu Chen, Yaran Li, Haoran Ma, Mingjun Zhao, Dongbin Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing100190 China University of Chinese Academy of Sciences Beijing100000 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

In autonomous driving and mobile robotic systems, obtaining the depths of objects in real-time is crucial. The current network-based methods usually design complex network to achieve 3D object detection or monocular depth estimation for the whole image, resulting in too slow to be applied to mobile robots. The perspective projection-based method can achieve real-time, which calculates the object depth based on the camera parameters, the object sizes in the world coordinates and in image coordinates. While it relies heavily on the accuracy of object size in images coordinates, and the size is usually obtained with errors through detector network. Combining the perspective projection-based methods and network-based methods, we propose a fast object depth estimation method by designing a neural network to learn perspective projection, called Fast-Depth-NPP: 1) Instead of considering the whole image, we only consider the local depth of the image;2) Using local image patches as network inputs avoids measurement errors of object size with detector;3) the use of global information is enhanced by incorporating position encoding. Our method is validated on the mobile robot public dataset Neurons Perception dataset, achieving excellent results and meeting the real-time requirements. © 2022 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Convection-UNet: A Deep Convolutional Neural Network for Convection Detection based on the Geo High-speed Imager of Fengyun-4B

Convection-UNet: A Deep Convolutional Neural Network for Con...

引用

Pattern Recognition, Machine Vision and Intelligent Algorithms (PRMVIA), International Conference on

作者： Yufei Wang Baihua Xiao The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences & University of Chinese Academy of Sciences Beijing China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Deep convection can cause a variety of severe weather conditions such as thunderstorms, strong winds, and heavy rainfall. Satellite observations provide all-weather and multi-directional observations, facilitating the timely detection of such weather systems, which is crucial to saving lives and property. However, previous methods based on channel feature extraction and threshold filtering did not make full use of information in satellite images, which led to limitations on such complex problems as strong convection detection. In this study, we propose a novel framework of a deep learning-based model Convection-UNet to detect convection. We use channel 4 to 7 of FY-4B GHI that we select according to the microphysical properties of convection as input and radar reflectivity as label. We combine the detailed training time and test time data augmentation strategies and build a deep neural network to automatically extract spatial context features and achieve end-to-end learning. Results show that the performance of our method far exceeds the previous channel extraction combined with threshold filtering methods such as BT and BTD at least 0.24 on Fi-measure. We also show that our channel selection and data augmentation strategies are of great significance to detect convection.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Spatially Dense Multi-Target Track Segment Association Algorithm

Spatially Dense Multi-Target Track Segment Association Algor...

引用

Chinese control Conference (CCC)

作者： Yan Yao Liping Yan Yuanqing Xia Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China

In the field of radar data processing, track interruption seriously affects target tracking, track fusion, and other tasks. The existing track segment association algorithms have low correlation accuracy in dense distributed or long-time interruption situations. To this purpose, a dense multi-target track segment association (DMTTSA) algorithm is proposed. Firstly, two identical networks based on the multi-head probability sparse (ProbSparse) self-attention are used to capture the long-term dependencies of the tracks. Then, the bidirectional quadruplet hard sample loss (BiQuaHard loss) is constructed to make the tracks belonging to the same targets closer and the tracks belonging to the different targets farther. Finally, DMTTSA takes the closest track pairs in the feature space as the associated tracks and divides the unassociated tracks into the birth and dead tracks in chronological order. Some comparative experiments are carried out to show the anti-noise performance of the DMTTSA, as well as the effectiveness of solving the problem of dense multi-target track interruption.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Effectiveness of Koopman Autoencoder Predicting Nonlinear System States: Effect of Latent Layer Neuron Number

Effectiveness of Koopman Autoencoder Predicting Nonlinear Sy...

引用

2022 Chinese Automation Congress, CAC 2022

作者： Zhou, Jun Jia, Yubin Liu, Zhimin Yong, Panxiao Guo, Jun The School of Automation Southeast University Jiangsu Nanjing210096 China The Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China

ISBN: (纸本)9781665465335

Researchers have always been popular with analyzing and controlling nonlinear systems, yet most methods are based on local linearized models. As an alternative, Koopman theory was introduced to solve global linearization problems. Koopman operator is infinite-dimensional and has the ability to globally linearize nonlinear systems without information loss. In this work, a Koopman autoencoder, which combines the Koopman operator and autoencoder network, is used for predicting nonlinear systems. The autoencoder network is designed to find an approximate finite-dimensional Koopman operator. An inverted pendulum dynamic system is used to evaluate the effectiveness of the Koopman autoencoder, and accurate prediction results have been achieved. Furthermore, we discussed the effect of latent layer neuron number in the Koopman autoencoder, prediction results are given, and the best number of latent layer neurons for this system is found. © 2022 IEEE.

关键词： Nonlinear systems

来源：评论

学校读者我要写书评

暂无评论

Implicit Scene Context-Aware Interactive Trajectory Prediction for Autonomous Driving

IEEE Transactions on Intelligent Vehicles

引用

IEEE Transactions on Intelligent Vehicles 2024年第9期9卷 5461-5477页

作者： Lan, Wenxing Li, Dachuan Hao, Qi Zhao, Dezong Tian, Bin Southern University of Science and Technology Research Institute of Trustworthy Autonomous Systems Shenzhen518055 China Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen518055 China University of Glasgow James Watt School of Engineering GlasgowG12 8QQ United Kingdom Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100190 China

The accurate prediction of behaviors of surrounding traffic participants is critical for autonomous vehicles (AV). How to fully encode both explicit (e.g., map structure and road geometry) and implicit scene context information (e.g., traffic rules) within complex scenarios is still challenging. In this work, we propose an implicit scene context-aware trajectory prediction framework (the PRISC-Net, Prediction with Implicit Scene Context) for accurate and interactive behavior forecasting. The novelty of the proposed approach includes: 1) development of a behavior prediction framework that takes advantage of both model- and learning-based approaches to fully encode scene context information while modeling complex interactions;2) development of a candidate path target predictor that utilizes explicit and implicit scene context information for candidate path target prediction, along with a motion planning-based generator that generates kinematic feasible candidate trajectories;3) integration of the proposed target predictor and trajectory generator with a learning-based evaluator to capture complex agent-agent and agent-scene interactions and output accurate predictions. Experiment results based on vehicle behavior datasets and real-world road tests show that the proposed approaches outperform state-of-the-art methods in terms of prediction accuracy and scene context compliance. © 2016 IEEE.

关键词： Trajectories

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：