检索结果-内蒙古大学图书馆

arXiv 2021年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Johansson, Karl H. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden Department of Electrical Engineering University of North Texas DentonTX76203 United States State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

In this paper, we consider a stochastic distributed nonconvex optimization problem with the cost function being distributed over n agents having access only to zeroth-order (ZO) information of the cost. This problem has various machine learning applications. As a solution, we propose two distributed ZO algorithms, in which at each iteration each agent samples the local stochastic ZO oracle at two points with a time-varying smoothing parameter. We show that the proposed algorithms achieve the linear speedup convergence rate O(√p=(nT)) for smooth cost functions under the state-dependent variance assumptions which are more general than the commonly used bounded variance and Lipschitz assumptions, and O(p=(nT)) convergence rate when the global cost function additionally satisfies the Polyak-Lojasiewicz (P-L) condition in addition, where p and T are the dimension of the decision variable and the total number of iterations, respectively. To the best of our knowledge, this is the first linear speedup result for distributed ZO algorithms, which enables systematic processing performance improvements by adding more agents. We also show that the proposed algorithms converge linearly under the relative bounded second moment assumptions and the P-L condition. We demonstrate through numerical experiments the efficiency of our algorithms on generating adversarial examples from deep neural networks in comparison with baseline and recently proposed centralized and distributed ZO algorithms. Copyright © 2021, The Authors. All rights reserved.

关键词： Cost functions

来源：评论

学校读者我要写书评

暂无评论

Distributed Nash Equilibrium Seeking in Coalition Games for Uncertain Euler-Lagrange Systems With Application to USV Swarm Confrontation

arXiv

引用

arXiv 2025年

作者： Yuwen, Cheng Wen, Guanghui Zhou, Jialing Luan, Meng Huang, Tingwen School of Automation Southeast University Nanjing210096 China State Key Laboratory of CNS/ATM Beijing Institute of Technology Beijing519088 China Department of System Science School of Mathematics Southeast University Nanjing211189 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen218055 China

In this paper, a coalition game with local and coupling constraints is studied for uncertain Euler-Lagrange (EL) systems subject to disturbances with unknown bounds. In the coalition game, each agent collaborates with other agents within the same coalition to optimize its coalition’s cost function while simultaneously competing against agents in other coalitions. Under a distributed framework where each agent has access only to its own action, cost function, and constraint parameters, a distributed strategy is proposed to seek the Nash equilibrium (NE). By combining adaptive methods and sign functions, model uncertainties and disturbances with unknown bounds in the EL system are compensated and suppressed, respectively. Furthermore, an integration of adaptive methods and consensus protocols is employed to update the Lagrange multipliers of both local and coupling constraints. A dynamic average consensus is employed to estimate the gradient of coalition function, while the leader-following protocol is adopted to estimate the actions of other agents. By leveraging Lyapunov theory, the NE is proven to be asymptotically stable. Moreover, an unmanned surface vehicle swarm confrontation is meticulously modeled and analyzed in the coalition game framework. A diverse array of tasks, including formation, encirclement, and interception, are systematically formulated. A numerical example demonstrates the effectiveness of the proposed algorithm. Copyright © 2025, The Authors. All rights reserved.

关键词： Lagrange multipliers

来源：评论

学校读者我要写书评

暂无评论

Acceleration command based visual servoing with artificial induced time-delay

Acceleration command based visual servoing with artificial i...

引用

2019 Conference on Advances in Robotics, AIR 2019

作者： Yadav, Madhu Kishore, Chimmula Kar, Indra Narayan Roy, Sumantra Dutta Control and Automation Group Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi India Computer Technology Group Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi India

ISBN: (纸本)9781450366502

The tracking of an object using visual feedback by controlling the camera motion is known as Visual Servoing. In general most of visual servoing techniques use camera velocity as control input. In this paper, camera acceleration is used for deriving the control law. The use of acceleration input can accomplish smoother operating trajectory. However, this controller requires the first order feature measurement which may not be available. In this paper, to circumvent the issue, a time-delayed approximation is used for the non-measurable system states. The controller parameters are obtained from the stability analysis of the closed-loop time-delay system using Lyapunov-Razumikhin approach. The implemented controller is able to track the desired feature smoothly. These results establish a complementary approach to the existing acceleration-based augmented controller design. © 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Visual servoing

来源：评论

学校读者我要写书评

暂无评论

Recursive Weighted Null-Space Fitting Method for Identification of Multivariate Systems ⁎

引用

IFAC-PapersOnLine 2021年第7期54卷 345-350页

作者： Mengyuan Fang Miguel Galrinho Håkan Hjalmarsson Zhejiang Engineering Laboratory of Industrial Internet Communication Technology Zhejiang Sci-Tech University Hangzhou China. State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China OHB Sweden AB Kista Sweden Centre for Advanced Bio Production and Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

Recursive identification of structured multivariate models is known to be difficult due to the general non-convexity of the likelihood function. In this work, we propose a recursive multivariate weighted null-space fitting method for identification of structured multivariate models. The proposed method first uses recursive least squares to estimate a high order non-parametric model, then a parametric model is obtained through weighted least squares from the non-parametric model. In this way, the method avoids directly optimizing a non-convex likelihood function and has guaranteed global convergency. Moreover, the proposed method is flexible in model structures and has the same finite sample performance as its off-line counterpart. We use simulation examples to illustrate the performance.

关键词： Recursive system identification multivariate systems weighted null-space fitting

来源：评论

学校读者我要写书评

暂无评论

Fault tolerance in networked systems through flexible task assignment

Fault tolerance in networked systems through flexible task a...

引用

Conference on control and Fault-Tolerant Systems (SysTol)

作者： Kai Schenk Jan Lunze Institute of Automation and Computer Control Ruhr-University Bochum Bochum Germany

ISBN: (纸本)9781728103815

This paper deals with networked control systems in which all subsystems have to fulfill a cooperative task. Based on the capabilities of each subsystem, a coordination unit evaluates how much a particular subsystem can contribute to the cooperative task. In case of a fault, the contribution of the faulty subsystem is re-evaluated and adjusted if necessary. As a result, the proposed method ensures the fulfillment of the cooperative task even in case of faults. A numerical example illustrates the functionality for a transportation system.

关键词： Task analysis Fault tolerant systems Fault tolerance Trajectory Transportation Switches Actuators

来源：评论

学校读者我要写书评

暂无评论

Plug-and-Play Based Optimization Algorithm for New Crime Density Estimation

引用

Journal of computer Science & Technology 2019年第2期34卷 476-493页

作者： Xiang-Chu Feng Chen-Ping Zhao Si-Long Peng Xi-Yuan Hu Zhao-Wei Ouyang School of Mathematics and Statistics Xidian University Xi’an 710126 China School of Mathematical Science Henan Institute of Science and Technology Xinxiang 453003 China Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing 100190 China Research Center of Beijing Visystem Co. Ltd. Beijing 100190 China

Different from a general density estimation,the crime density estimation usually has one important factor:the geographical *** this paper,a new crime density estimation model is formulated,in which the regions where crime is impossible to happen,such as mountains and lakes,are *** further optimize the estimation method,a learning-based algorithm,named Plug-and-Play,is implanted into the augmented Lagrangian scheme,which involves an off-the-shelf filtering *** selections of the filtering operator make the algorithm correspond to several classical estimation ***,the proposed Plug-and-Play optimization based estimation algorithm can be regarded as the extended version and general form of several classical *** the experiment part,synthetic examples with different invalid regions and samples of various distributions are first *** under complex geographic constraints,we apply the proposed method with a real crime dataset to recover the density *** state-of-the-art results show the feasibility of the proposed model.

关键词： crime density estimation augmented Lagrangian strategy Plug-and-Play filtering operator

来源：评论

学校读者我要写书评

暂无评论

Execution of smart electric vehicle charging station driven by RE technology using soft computing approach 3

Execution of smart electric vehicle charging station driven ...

引用

3rd IEEE International Virtual Conference on Innovations in Power and Advanced Computing Technologies, i-PACT 2021

作者： Kumar, K. Vinoth Sujitha, S. Stalin, B. Buvana, D. Josh, F.T. Vinodha, K. Ramya, K.C. Saravanakumar, R. Logeswaran, D. New Horizon College of Engineering Department of Electrical and Electronics Engineering Bengaluru India Dr. MGR Polytechnic College Department of Electrical and Electronics Engineering Arni India Dhanalakshmi College of Engineering Department of Electrical and Electronics Engineering Chennai India Karunya Institute of Technology and Sciences Department of Electrical and Electronics Engineering Coimbatore India PES University Electronic City Campus Department of Computer Science Engineering Bengaluru India Sri Krishna College of Engineering and Technology Department of Electrical and Electronics Engineering Coimbatore India School of Electrical Engineering Vellore Institute of Technology Department of Control and Automation Vellore India Kongu Engineering College Department of Electrical and Electronics Engineering Perundurai India

ISBN: (纸本)9781665426916

This paper outlines potential demand for electric vehicles, charging station infrastructure and its challenges for the India scenario, as well as the increasing liberalization and expansion of production, transmission and distribution. Distributed and renewable electricity generation and distribution, as well as market processes related to energy allocation and energy mix. is the subject of evolutionary development with improved performance and reliability. Structural analysis of respective parameters was performed for the commercial scope of electric vehicles in the existing energy market and regulatory concerns are taken into account to describe a scenario in which a company global control of electric vehicle charging and service provision of ancillary networks. Experimental results show confirmatory results. © 2021 IEEE.

关键词： Commercial vehicles

来源：评论

学校读者我要写书评

暂无评论

Quadrotor Tracking control: Design and Experiments

Quadrotor Tracking Control: Design and Experiments

引用

control Technology and Applications (CCTA),

作者： Michael Schwung Daniel Vey Jan Lunze Institute of Automation and Computer Control Ruhr-Universität Bochum Germany

This paper proposes a design method for a two degrees-of-freedom tracking controller for a quadrotor to ensure trajectory following. The controller consists of two parts. A flatness-based feedforward controller ensures trajectory tracking of the undisturbed vehicle and a feedback controller composed of an altitude controller and a position and attitude controller in a cascaded structure compensates the tracking error due to disturbances and model uncertainties. The feedback controller is designed with the root locus method based on the linearized model of the quadrotor. Experiments are made in a testbed under windy conditions with a bounded windforce. The results show that the quadrotor with the proposed controller follows a given trajectory closely with small, bounded deviations, which can be estimated in advance with the model of the quadrotor.

关键词： Trajectory Adaptive control Uncertainty Computational modeling Adaptation models Attitude control Unmanned aerial vehicles

来源：评论

学校读者我要写书评

暂无评论

TDNCIB: Target-Driven Navigation with Convolutional Information Branch Based on Deep Reinforcement Learning

TDNCIB: Target-Driven Navigation with Convolutional Informat...

引用

Chinese automation Congress (CAC)

作者： Xinzhou Zhao Tian Wang Kexin Liu Mengyi Zhang Peng Shi Hichem Snoussi School of Automation Science and Electrical Engineering Beihang University Beijing China Institute of Artificial Intelligence Beihang University Beijing China College of Electrical Engineering and Control Science Nanjing Tech University Nanjing China School of Mathematics and Computer Science Fujian Normal University Fujian China Institute Charles Delaunay-LM2S University of Technology of Troyes Troyes France

ISBN: (纸本)9781665426480

Target-driven navigation has been a significant application field of reinforcement learning. However, sparse reward and lack of useful environment information are still existing problems. Therefore, in this paper, we propose a novel design to the target-driven visual navigation based on deep reinforcement learning: Target-Driven Navigation with Convolutional Information Branch (TDNCIB), which enriches the high-dimensional information learned by the network from the environment. It is an improvement of A2C algorithm. CIB can help make full use of environmental information and serve as a complement to the baseline. Besides, a novel reward design using similarity is introduced to relieve sparse reward. The ablation study is implemented in 4 different scenes of AI2-THOR framework comparing the baseline and our TDNCIB. According to our evaluation, TDNCIB converges faster than the baseline and achieves better performance in 5 common metrics with shorter trajectory length, less collision and higher success rate.

关键词： Measurement Visualization automation Navigation Reinforcement learning Trajectory

来源：评论

学校读者我要写书评

暂无评论

Deep learning of Hash Method for Fast Image Retrieval

Deep learning of Hash Method for Fast Image Retrieval

引用

Chinese automation Congress (CAC)

作者： Taiying Peng Tian Wang Kexin Liu Mengyi Zhang Peng Shi Hichem Snoussi School of Automation Science and Electrical Engineering Beihang University Beijing China Institute of Artificial Intelligence Beihang University Beijing China College of Electrical Engineering and Control Science Nanjing Tech University Nanjing China School of Mathematics and Computer Science Fujian Normal University Fujian China Institute Charles Delaunay-LM2S University of Technology of Troyes Troyes France

ISBN: (纸本)9781665426480

Most of the image retrieval technology are complex and advanced methods to improve the accuracy of retrieval. They also have deep net layers, which costs much time to caculate the result. When we need deal with complex image task, it will be hard to complete the fast image *** paper presents a convolutional neural network combining with the fast encoding technology under the hash algorithm to improve fast retrieval time and accuracy. In order to keep the existing accuracy and retrieval speed of the network, we present a Hash method path of the network combining witn the dual networks. By clustering analysis and AlexNet,we get lots of high dimensional feature. Then these feature is put into Hash-coding algorithm. The algorithm will output binary feature to match the target image. Through learning similar graph pairs, Hash net work shorten the distance between the similar images, and achieve fast clustering. Then it realizes image retrieval and outputs the most similar picture. Complete the search task.

关键词： Training Deep learning Image coding Costs Image retrieval Clustering algorithms Feature extraction

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：