检索结果-内蒙古大学图书馆

2021 China automation Congress, CAC 2021

作者： Liu, Yue Xiong, Gang Zhu, Fenghua Chen, Shichao Zhang, Liguo Liu, Xudong School of Artificial Intelligence and Automation Beijing University of Technology The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation The Cloud Computing Center Chinese Academy of Sciences Beijing China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Qingdao Academy of Intelligent Industries Chinese Academy of Sciences Beijing China Faculty of Information and Technology Beijing University of Technology Beijing China

ISBN: (纸本)9781665426473

In the face of the rapid development of the IoT, the traditional cloud computing, while providing services for mobile intelligent devices, also brings problems such as network bandwidth occupation and communication delay. Edge computing can solve these problems to some extent. But too many offloaded tasks may result in an edge server becoming overloaded and execution delay of tasks increasing, the computing resources of idle edge devices are also not fully utilized. In order to make full use of the computing resources of idle edge devices in the local network and reduce the execution delay for computing tasks, this paper takes the average delay time for all end devices as the optimization objective and proposes an end-edge cooperative scheduling (EECS) model to schedule tasks for edge computing. The scheduling algorithm used in EECS model is improved based on MCT algorithm. We use the EdgeCloudSim to verify the EECS model and scheduling algorithm. The simulation results show that the average completion time of computing tasks in EECS model, compared with only single edge server (SEE) task computing model, can be reduced by up to three times. In addition, the system load can be balanced to a certain extent in local network. © 2021 IEEE

关键词： Edge computing

来源：评论

学校读者我要写书评

暂无评论

Parallel control for Optimal Tracking via Adaptive Dynamic Programming

引用

IEEE/CAA Journal of Automatica Sinica 2020年第6期7卷 1662-1674页

作者： Jingwei Lu Qinglai Wei Fei-Yue Wang School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 The State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078 Qingdao Academy of Intelligent Industries Qingdao 266109China

This paper studies the problem of optimal parallel tracking control for continuous-time general nonlinear *** existing optimal state feedback control,the control input of the optimal parallel control is introduced into the feedback ***,due to the introduction of control input into the feedback system,the optimal state feedback control methods can not be applied *** address this problem,an augmented system and an augmented performance index function are proposed ***,the general nonlinear system is transformed into an affine nonlinear *** difference between the optimal parallel control and the optimal state feedback control is analyzed *** is proven that the optimal parallel control with the augmented performance index function can be seen as the suboptimal state feedback control with the traditional performance index ***,an adaptive dynamic programming(ADP)technique is utilized to implement the optimal parallel tracking control using a critic neural network(NN)to approximate the value function *** stability analysis of the closed-loop system is performed using the Lyapunov theory,and the tracking error and NN weights errors are uniformly ultimately bounded(UUB).Also,the optimal parallel controller guarantees the continuity of the control input under the circumstance that there are finite jump discontinuities in the reference ***,the effectiveness of the developed optimal parallel control method is verified in two cases.

关键词： Adaptive dynamic programming(ADP) nonlinear optimal control parallel controller parallel control theory parallel system tracking control neural network(NN)

来源：评论

学校读者我要写书评

暂无评论

An Introduction to Domain Adaptive Object Detection from Synthesis to Reality

An Introduction to Domain Adaptive Object Detection from Syn...

引用

第40届中国控制会议

作者： Zhijun Xue Wenjie Chen Jing Li State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center

In recent years,deep learning based object detection has achieved great *** methods typically assume that large amount of labeled training data is available,meanwhile,training and test data are independent and identically ***,the two assumptions are not always hold in *** many applications,it is prohibitively expensive and time-consuming to obtain large quantities of labeled *** computer graphics technology to generate a large number of labeled data provides a solution to this ***,direct transfer across domains from synthesis to reality often performs poorly due to the presence of domain *** adaptive object detection are concerned with accounting for these types of *** this paper,we present an introduction to these ***,we briefly introduce the object detection and domain ***,the synthetic object detection datasets and related software tools are ***,we present a categorization of approaches,divided into discrepancy-based methods,adversarial discriminative methods,reconstruction-based methods and ***,we also discuss some potential deficiencies of current methods and several open problems which can be explored in future work.

关键词： Deep learning Object detection Synthesis to reality Domain adaptation

来源：评论

学校读者我要写书评

暂无评论

Action Recognition Algorithm based on 2D Human Pose Estimation Method

Action Recognition Algorithm based on 2D Human Pose Estimati...

引用

第40届中国控制会议

作者： Chongkai Yu Wenjie Chen Ye Li Chen Chen State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center

This paper presents an action recognition method based on 2D human body node data in video. This method uses the pose estimation algorithm to detect the human body node data in each frame of video information. We get the two-dimensional coordinates and confidence data of the nodes, and optimize the arrangement of these data into a 3D array form similar to ***, we use the classical two-dimensional convolutional neural network to carry out classification training. The test on UCF-101 data set shows that this method can indeed improve the accuracy of action recognition based on RGB information to a certain extent, and reduce the training cost.

关键词： Action recognition Pose estimation Two-dimensional convolutional neural network

来源：评论

学校读者我要写书评

暂无评论

Distributed Event-Triggered Bandit Convex Optimization With Time-Varying Constraints

引用

IEEE Transactions on control of Network systems 2025年

作者： Zhang, Kunpeng Yi, Xinlei Wen, Guanghui Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Ministry of Education Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Shanghai201210 China Southeast University School of Automation Nanjing210096 China University of Groningen Engineering and Technology Institute Groningen Faculty of Science and Engineering GroningenAG 9747 Netherlands KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm10044 Sweden KTH Royal Institute of Technology Digital Futures Stockholm10044 Sweden

This paper considers the distributed bandit convex optimization problem with time-varying inequality constraints over a network of agents, where the goal is to minimize network regret and cumulative constraint violation. Existing distributed online algorithms solving this problem require that each agent broadcasts its decision to its neighbors at each iteration. However, communication resources are often limited. To better utilize communication resources, we propose a distributed event-triggered online primal-dual algorithm with two-point bandit feedback. Under several classes of appropriately chosen decreasing parameter sequences and non-increasing event-triggered threshold sequences, we establish dynamic network regret and network cumulative constraint violation bounds. These bounds are comparable to the results achieved by distributed event-triggered online algorithms with full-information feedback. Finally, a numerical example is provided to verify the theoretical results. © 2014 IEEE.

关键词： Optimization algorithms

来源：评论

学校读者我要写书评

暂无评论

Model Compression Based on YOLOv3 Object Detection Algorithm from the Perspective of UAV

Model Compression Based on YOLOv3 Object Detection Algorithm...

引用

第40届中国控制会议

作者： Bing Wu Zhijun Xue Wenjie Chen State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center

Recently,unmanned aerial vehicles are widely used in surveillance,aerial photography,power grid line inspections and other *** order to deploy the YOLOv3[1] algorithm on drones,it is necessary to adopt the YOLOv3 algorithm with fewer parameters and a simpler *** paper implements the model compression of YOLOv3 based on methods such as sparseness,pruning,and knowledge *** paper implements the sparseness of the network by adding L1 regular expressions on the convolutional *** that,redundant channels and layers are removed through channel pruning and layer *** sparse and pruning,the mAP lost a *** using knowledge distillation after pruning,it attempts to recover mAP lost in sparseness and *** this method,the YOLOv3 algorithm can be deployed on embedded platforms such as RK3399 *** evaluate the model on the visdrone2019 *** experimental results show that after model compression,YOLOv3 is more suitable for deployment on embedded platforms.

关键词： Object Detection Model Compress RK3399pro YOLOv3

来源：评论

学校读者我要写书评

暂无评论

Event-triggered Extended Kalman Filter for UAV Monitoring system

Event-triggered Extended Kalman Filter for UAV Monitoring Sy...

引用

Data Driven control and Learning systems (DDCLS)

作者： Yunge Zang Yan Li Yuting Duan Xiangyu Li Xi Chang Zhen Li Beijing Aerospace Automatic Control Institute Beijing P. R. China National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing P. R. China Beijing Aerospace Institute for Metrology and Measurement Technology Beijing P. R. China Key Laboratory for Intelligent Control … Decision on Complex Systems School of Automation Beijing Institute of Technology Beijing China

To facilitate ground station monitoring and command uploading, unmanned aerial vehicles (UAVs) need to frequently exchange individual state data between units. However, this results in a significant usage of communication bandwidth. To address this issue, on the basis of an event-triggered strategy, this paper proposes an Extended Kalman Filter (EKF). aimed at reducing the communication burden of UAVs while maintaining high accuracy. Specifically, a state measurement triggered by an event is selected for filtering only if it contains innovation, thereby reducing the amount of data that needs to be communicated. Since UAV systems are nonlinear, EKF is adopted to fully utilize the information obtained from event-triggered strategies, thereby enhancing the estimation performance. In this paper, a physical UAV was used to verify the proposed algorithm, and it proved to have robust dynamic performance and to effectively reduce the communication rate.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Path Planning of Mobile Robot Based on an Improved Genetic Algorithm 2

Path Planning of Mobile Robot Based on an Improved Genetic A...

引用

2nd IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2022

作者： Chen, Zenghua Xiong, Gang Liu, Sheng Shen, Zhen Li, Yue Institute of Automation Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Chang'an University School of Automobile Xi'an China

ISBN: (纸本)9781665492270

In order to solve the problem of premature convergence of the basic genetic algorithm when planning the robot running path, the basic genetic algorithm is improved and optimized. Different population initialization methods are used to initialize multiple populations randomly, so as to improve the diversity of populations;Improve the adaptive strategy and elite strategy of crossover and mutation operators to improve the convergence speed of the algorithm;Add the path tortuosity as the planning index in the fitness function to make the planned path smoother, and add constraints to the model to avoid obstacles;Finally, through the transformation of the coding paradigm of the above improved genetic algorithm, it can run on Flink distributed cluster to obtain faster solution speed, so as to meet the efficiency requirements of path planning in large-scale robot cluster system. The optimized algorithm is compared with the basic genetic algorithm. The simulation results show that the improved algorithm is efficient in robot path planning. © 2022 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Capacity Optimization of a Hybrid Energy Storage system Considering Wind-Solar Reliability Evaluation Based on a Novel Multi-Strategy Snake Optimization Algorithm

SSRN

引用

SSRN 2022年

作者： Wang, Chen Jiao, Shangbin Li, Yujun Zhang, Qing School of Automation and Information Engineering Xi’an University of Technology Xi’an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China

When the capacity configuration of a hybrid energy storage system (HESS) is optimized considering the reliability of a wind turbine and photovoltaic generator (PVG), the sequential Monte Carlo method is typically adopted to simulate the normal operation and fault probability of wind turbines and PVG units. The capacity optimization configuration model of the HESS is constructed with the life cost cycle (LCC) as an objective and the loss of power supply probability (LPSP) as constraints. The variational mode decomposition is used to decompose the unbalanced power in the wind-PV microgrid. The maximum power of the optimized the battery bank and the supercapacitor bank are used to determine the frequency division point, and the high-frequency power and low-frequency power are respectively allocated to the supercapacitor bank and the battery bank. When the snake optimizer (SO) is used to solve the nonconvex capacity optimization configuration model of the HESS, poor accuracy and stability are significant problems. The opposition-based learning, adaptive weight factor, and Lévy flight strategy are introduced in the algorithm framework. Twenty-three test functions show that multi strategy snake optimizer (MSO) significantly improves the accuracy and convergence speed compared with SO. Nine optimization algorithms including MSO are used to solve the capacity optimization problem of the HESS. The results show that MSO is superior to other algorithms in performance and numerical accuracy. It can reduce the LCC 4.5% and ensure that the capacity of the HESS meets the load demand when the wind turbine and PVGs are in a fault state. © 2022, The Authors. All rights reserved.

关键词： Variational mode decomposition

来源：评论

学校读者我要写书评

暂无评论

LU2Net: A Lightweight Network for Real-time Underwater Image Enhancement

arXiv

引用

arXiv 2024年

作者： Yang, Haodong Xu, Jisheng Lin, Zhiliang He, Jianping The Department of Computer Science Shanghai Jiao Tong University China The Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China The School of Ocean and Civil Engineering Shanghai Jiao Tong University State Key Laboratory of Ocean Engineering Shanghai200240 China

Computer vision techniques have empowered underwater robots to effectively undertake a multitude of tasks, including object tracking and path planning. However, underwater optical factors like light refraction and absorption present challenges to underwater vision, which cause degradation of underwater images. A variety of underwater image enhancement methods have been proposed to improve the effectiveness of underwater vision perception. Nevertheless, for real-time vision tasks on underwater robots, it is necessary to overcome the challenges associated with algorithmic efficiency and real-time capabilities. In this paper, we introduce Lightweight Underwater Unet (LU2Net), a novel U-shape network designed specifically for real-time enhancement of underwater images. The proposed model incorporates axial depthwise convolution and the channel attention module, enabling it to significantly reduce computational demands and model parameters, thereby improving processing speed. The extensive experiments conducted on the dataset and real-world underwater robots demonstrate the exceptional performance and speed of proposed model. It is capable of providing well-enhanced underwater images at a speed 8 times faster than the current state-of-the-art underwater image enhancement method. Moreover, LU2Net is able to handle real-time underwater video enhancement. Copyright © 2024, The Authors. All rights reserved.

关键词： Motion planning

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：