检索结果-内蒙古大学图书馆

2023 China Automation Congress, CAC 2023

作者： Wu, Yining Zhang, Runfeng Liu, Fang Liu, Zhenzhong Wu, Jianguo Dong, Haonan School of Mechanical Engineering Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin300384 China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education China Yichang Research Institute of Testing Technology Yichang443003 China Tianjin Hanhailanfan Marine Technology Co. Ltd. Tianjin300457 China School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9798350303759

Waves seriously impact port construction, worldwide route planning, military activities, and wave power generation. To improve the accuracy of significant wave height prediction, we proposed a novel prediction method, a multi-layer perceptron combined with a backpropagation adjustment (MLP-BP) prediction model that combines mutation mode decomposition (VMD) and a simulated annealing optimization algorithm (SA). Firstly, we use the variable modulus method to decompose the significant wave height sequence data and transform the wave height sequence into multiple different sub-modes (IMF) to reduce the complexity and non-stationarity of the data. Secondly, the simulated annealing algorithm (SA) is used to optimize the weight and bias of the MLP-BP neural network to find the optimal parameter configuration and improve the performance and generalization ability of the prediction model. Finally, the decomposed sub-modal components of each significant wave height sequence are inserted into the MLP-BP neural network and the predicted values of each element are summed to obtain the final significant wave height prediction. The prediction results of the SSA-MLP-BP, PSO-MLP-BP, SA-MLP-BP, and VMD-SA-MLP-BP were compared and demonstrated that the VMD-SA-MLP-BP model performed best. The MAE, MAPE, MSE, RMSE, and R2 of the prediction evaluation indexes were 0.036 m, 11.7%, 0.004 m2, 0.067 m, and 0.983, respectively, which performed well in predicting significant wave height. © 2023 IEEE.

关键词： Variational mode decomposition

来源：评论

学校读者我要写书评

暂无评论

Stability Analysis and Performance Evaluation of Delayed Bilateral Telerobotic systems over a Lossy Communication Channel

引用

Journal of systems Science & Complexity 2021年第1期34卷 157-179页

作者： BAKHSHI Ali ALFI Alireza TALEBI Heidar Ali SOURATGAR Amir Aboulfazl YOUSEFI Mahdi Faculty of Electrical and Robotic Engineering Shahrood University of TechnologyShahrood 36199-95161Iran Power Plants Control Systems Technology Development Plan Department of monitoring and ControlNiroo Research InstituteTehran 14665-517Iran Real-Time and Robotics system Laboratory Faculty of Electrical EngineeringAmirkabir University of TechnologyHafez AvenueTehran 15914Iran Electrical and Computer Engineering Department The University of British Columbia2385East MallVan couverBC V6T 1Z4Canada

The focus of this paper is to address a novel control technique for stability and transparency analysis of bilateral telerobotic systems in the presence of data loss and time delay in the communication channel. Different control strategies have been reported to compensate the effects of time delay in the communication channel;however, most of them result in poor performance under data loss. First, a model for data loss is proposed using a finite series representation of a set of periodic continuous *** improve the performance and data reconstruction, a holder circuits is also introduced. The passivity of the overall system is provided via the wave variable technique based on the proposed model for the data loss. The stability analysis of the system is then derived using the Lyapunov theorem under the time delay and the data loss. Finally, experimental results are given to illustrate the capability of the proposed control technique.

关键词： Lossy channel passivity stability telerobotic transparency

来源：评论

学校读者我要写书评

暂无评论

Sample-Wise Graph-Based Multivariate Short-Term PV Power Forecasting

引用

IEEE Transactions on Sustainable Energy 2025年

作者： Wang, Xuguang Liu, Wangjie Ni, Junhong Zhang, Mi North China Electric Power University School of Control and Computer Engineering Baoding key Laboratory of State Detection and Optimization Regulation for Integrated Energy System Hebei Technology Innovation Center of Simulation & Optimized Control for Power Generation Baoding 071003 China North China Electric Power University School of Electrical and Electronic Engineering Baoding 071003 China

Reliable short-term photovoltaic (PV) power forecasting is of crucial significance for the rational dispatching of power sources and the effective control of operating costs for the power grid. However, temporal misalignment and regression accuracy imbalance of PV power data pose significant challenges to the reliability of forecast results. In this study, multivariate PV power forecasting is investigated from the perspective of forecast model samples. Firstly, the extent of misalignment of a sample is parameterized by a time-delay vector. Subsequently, the sample-wise graph is defined to relate the time-delay vector with PV power data. Then, the time-delay vector is estimated by minimizing the smoothness metric of the sample-wise graph. Finally, a sample-wise graph-based sample weighting strategy is introduced to address the issue of regression accuracy imbalance. The efficiency of the proposed PV power forecasting scheme is validated through extensive experiments on real-world datasets. Comparison experiments suggest that the proposed scheme can achieve remarkably improved short-term PV power forecasting. © 2010-2012 IEEE.

关键词： PV power forecasting Regression accuracy imbalance Sample temporal misalignment Sample-wise graph Time-delay estimation

来源：评论

学校读者我要写书评

暂无评论

Scalable second-order consensus of hierarchical groups

arXiv

引用

arXiv 2024年

作者： Wang, Jiamin Liu, Jian Xiao, Feng Xi, Ning Zheng, Yuanshi Shaanxi Key Laboratory of Space Solar Power Station System School of Mechano-Electronic Engineering Xidian University Xi’an710071 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China School of Cyber Engineering Xidian University Xi’an710071 China

Motivated by widespread dominance hierarchy, growth of group sizes, and feedback mechanisms in social species, we are devoted to exploring the scalable second-order consensus of hierarchical groups. More specifically, a hierarchical group consists of a collection of agents with double-integrator dynamics on a directed acyclic graph with additional reverse edges, which characterize feedback mechanisms across hierarchical layers. As the group size grows and the reverse edges appears, we investigate whether the absolute velocity protocol and the relative velocity protocol can preserve the system consensus property without tuning the control gains. It is rigorously proved that the absolute velocity protocol is able to achieve completely scalable second-order consensus but the relative velocity protocol cannot. This result theoretically reveals how the scalable coordination behavior in hierarchical groups is determined by local interaction rules. Moreover, we develop a hierarchical structure in order to achieve scalable second-order consensus for networks of any sizes and with any number of reverse edges. © 2024, CC BY.

关键词： Feedback control

来源：评论

学校读者我要写书评

暂无评论

Energy Management Based on Multi-Agent Deep Reinforcement Learning for A Multi-Energy Industrial Park

arXiv

引用

arXiv 2022年

作者： Zhu, Dafeng Yang, Bo Liu, Yuxiang Wang, Zhaojian Ma, Kai Guan, Xinping Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao066004 China

Owing to large industrial energy consumption, industrial production has brought a huge burden to the grid in terms of renewable energy access and power supply. Due to the coupling of multiple energy sources and the uncertainty of renewable energy and demand, centralized methods require large calculation and coordination overhead. Thus, this paper proposes a multi-energy management framework achieved by decentralized execution and centralized training for an industrial park. The energy management problem is formulated as a partially-observable Markov decision process, which is intractable by dynamic programming due to the lack of the prior knowledge of the underlying stochastic process. The objective is to minimize long-term energy costs while ensuring the demand of users. To solve this issue and improve the calculation speed, a novel multi-agent deep reinforcement learning algorithm is proposed, which contains the following key points: counterfactual baseline for facilitating contributing agents to learn better policies, soft actor-critic for improving robustness and exploring optimal solutions. A novel reward is designed by Lagrange multiplier method to ensure the capacity constraints of energy storage. In addition, considering that the increase in the number of agents leads to performance degradation due to large observation spaces, an attention mechanism is introduced to enhance the stability of policy and enable agents to focus on important energy-related information, which improves the exploration efficiency of soft actor-critic. Numerical results based on actual data verify the performance of the proposed algorithm with high scalability, indicating that the industrial park can minimize energy costs under different demands. © 2022, CC BY-NC-ND.

关键词： Multi agent systems

来源：评论

学校读者我要写书评

暂无评论

Att-TCN: An Advertising Attribution Method Based on Temporal Convolutional Network with Attention Mechanism

Att-TCN: An Advertising Attribution Method Based on Temporal...

引用

International Conference on computer and Communications (ICCC)

作者： Bowen Xie Yi Sun Zhaowen Lin Baoquan Ma School of Computer Science (National Pilot Software Engineering School) Beijing University of Posts and Telecommunications Beijing China National Engineering Laboratory for Mobile Network Technologies Beijing China National Computer System Engineering Research Institute of China Beijing China National Engineering Laboratory for Industry Control System Information Security Technology Beijing China

Advertising attribution is an effective method to measure the effect of various advertisements in the era of Internet advertising. It enables scientific tracking back and refined operation of advertising by quantitatively evaluating the contribution of different advertising channels to reach the target. It is challenging to predict conversion results based on users' journey data accurately, reflect the impact of ads on user conversions, and appropriately assign attribution values to advertising channels. To achieve the above objectives, we propose an advertising attribution method based on a temporal convolutional network with an attention mechanism (Att-TCN). By mining the hidden information in time and attribution channels using the attention mechanism, our proposed method can improve the accuracy of conversion prediction and thus more rationally assign attribution values across channels. Experimental validation on a real dataset obtained from an operational commercial advertising monitoring company shows that our proposed attribution method has better accuracy than other state-of-the-art attribution methods and gives an open-ended approach to attribution value assignment.

关键词： Target tracking Costs Companies Predictive models Internet Convolutional neural networks Data mining

来源：评论

学校读者我要写书评

暂无评论

Online Scheduling in Virtualized TSN Networks via Joint Admission control and VNF Embedding

Online Scheduling in Virtualized TSN Networks via Joint Admi...

引用

IEEE International Conference on Communications in China (ICCC)

作者： Yajing Zhang Cailian Chen Chaoqun You Mingyan Li Xinping Guan Tony Q. S. Quek Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai P. R. China School of Computer Science Fudan University College of Computer Science Chongqing University Chongqing P. R. China Information Systems Technology and Design Singapore University of Technology and Design Singapore

ISBN: (数字)9798350378412

ISBN: (纸本)9798350378429

Introducing virtualization enhances the flexibility of time-sensitive networking (TSN), wherein applications manifest as service function chains comprising a series of virtual network functions (VNFs). However, such virtualized TSN realizes determinacy through global configuration, being too complicated to serve dynamic applications in time. To address this issue, we innovatively propose to achieve TSN scheduling by distributively executing admission control (AC), whereby the scheduling complexity is radically reduced. Specifically, we first build a two-way AC model that captures TSN multi-queue characteristics. Then, we define admissible regions of nodes and links, working as metrics for AC decision-making and enabling feasible TSN scheduling. Built upon this, we propose a joint AC and VNF embedding mechanism, Rapid Admission control (RapidAC), which consists of two algorithms. The first algorithm responds to dynamic applications rapidly and derives node-mapping solutions by judging nodes’ admissible regions. Based on this, the second algorithm augments the detailed VNF embedding solution according to admissible regions of links. Simulation results show that RapidAC reduces runtime by 90% compared with existing TSN scheduling algorithms.

关键词： Measurement Runtime Scheduling algorithms Service function chaining Heuristic algorithms Simulation Admission control

来源：评论

学校读者我要写书评

暂无评论

sEMG-vision Tra: A Gesture Recognition Method Based on Surface EMG Signal-Vision Fusion

sEMG-vision Tra: A Gesture Recognition Method Based on Surfa...

引用

IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Weili Ding Shuhui Zhang Han Liu Engineering Research Center of Intelligent Control System and Intelligent Equipment Ministry of Education Laboratory of Intelligent Rehabilitation and Neromodulation of Hebei Province Institute of Electrical Engineering Yanshan University Qinhuangdao People's Republic of China College of Computer Science and Software Engineering Shenzhen University Shenzhen People's Republic of China

ISBN: (数字)9798350379167

ISBN: (纸本)9798350379174

To address the challenges of gesture recognition accuracy within human-computer interaction technologies, and to overcome the limitations of single-modal biometric feature recognition - which often falls short in practical applications, this paper introduces a multimodal feature fusion classification algorithm, sEMG-vision Tra. This algorithm aims to integrate different types of biometric data, thereby enhancing the robustness and effectiveness of gesture recognition. Initially, we utilize the Mediapipe framework to extract skeletal point data from images of the human hand. The next process involves calculating distance and angle features between skeletal points, as well as extracting time-domain features from surface electromyographic (sEMG) signals. Following this, features from these two modalities are concatenated along the feature dimension and then linearly projected onto the target dimension. To effectively capture the intricate interrelationships among these features, we employ a multi-layer Transformer encoder for encoding the combined features. The encoded features are subsequently mapped to the final output dimension. The effectiveness of our approach is demonstrated through validation on a custom dataset. This algorithm's key contribution lies in the fusion of two distinct modal features, images and EMG signals, to achieve a more holistic and precise feature representation. By this, it significantly enhances our ability to capture the essential information for applications like gesture recognition or human-computer interaction. The algorithm showcases exceptional performance, achieving a noteworthy accuracy rate of 95.56% on a custom dataset.

关键词： Human computer interaction Biometrics Visualization Accuracy Gesture recognition Feature extraction Transformers Electromyography Classification algorithms Time-domain analysis

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

Joint Transmission for Industrial 5G-TSN Networks: A Deep Graph Clustering Approach

Joint Transmission for Industrial 5G-TSN Networks: A Deep Gr...

引用

IEEE International Conference on Communications in China (ICCC)

作者： Mingyan Li Houling Liu Chao Chen Fuqiang Gu Songtao Guo Xinping Guan College of Computer Science Chongqing University Chongqing P. R. China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai P. R. China Department of Automation Shanghai Jiao Tong University Shanghai P. R. China

ISBN: (数字)9798350378412

ISBN: (纸本)9798350378429

The integration of 5G and time-sensitive networking (TSN) is a promising technology to provide ubiquitous connection and deterministic transmission for industrial internet of things (IIoT), However, the seamless flow transmission of 5G-TSN is challenging as it requires joint modeling of frequency multiplexing in 5G and time-access in TSN with the scheduling resolution mis-match of the considered systems. To address this issue, this paper focuses on the integrated enhancement of 5G and TSN by optimizing the flow transmission of age-aware monitoring systems with the protocols of 5G grant-free uplink and TSN cyclic queuing and forwarding (CQF) considered. Then, an age-aware flow clustering scheme, STage, is proposed based on deep graph clustering. STage allows each system transmitting in a grant-free and distributed manner on the resources of a pre-allocated configured-grant (CG), that best suits its spatial realization in terms of 5G device relative location as well as the TSN delivery path. Based on the techniques of graph attentional autoencoder and interference-aware self-clustering, STage can jointly optimize the end-to-end 5G-TSN transmission by reducing the CQF queue overflow in TSN and the co-channel interference in 5G. Simulations show that STage can assist 5G-TSN integrated networks offering superior transmission capabilities under the limited spectrum and queue resources.

关键词： Protocols Job shop scheduling 5G mobile communication Frequency division multiplexing Uplink Interchannel interference Monitoring

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：