检索结果-内蒙古大学图书馆

Data-driven output regulation control for constrained linear systems

Science China(Information Sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

来源：评论

学校读者我要写书评

暂无评论

Application of a digital intelligent assistant to support industrial processes: The case of adaptive allocation in the face of cyber attacks 6

Application of a digital intelligent assistant to support in...

引用

6th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Colabianchi, Silvia Department of Computer Control and Management Engineering Antonio Ruberti Via Ariosto 25 Rome00185 Italy

The research proposes the application of Digital Intelligent Assistants (DIAs) as proactive agents that can support employees in dealing with cybersecurity issues in sustainable industrial processes underlying the importance of a fruitful Human-Artificial Intelligence collaboration. Cyber-attacks around the world are constantly increasing. DIAs are becoming more effective, also thanks to the use of Large Language Models. Users are required to recall security procedures and rules. Moreover, attacks are constantly evolving and following different patterns. The study presents how a DIA can be a backup agent during and after an attack. The application of digital intelligent assistance technology helps to reduce the cognitive load and pressure that users feel during downtime. In addition, the solution enhances attack reporting by decreasing the shame experienced by the victims. The research proposes a methodological design defining the agent's technical and functional characteristics and its adaptive relationship with human characteristics. The solution is developed using the RASA framework and evaluated through a case study based on a phishing attack scenario. © 2025 The Authors. Published by Elsevier B.V.

关键词： Chatbots

来源：评论

学校读者我要写书评

暂无评论

Optimal Strategies to Contain Arboviruses Spread

引用

SN computer Science 2025年第5期6卷 1-13页

作者： Di Giamberardino, Paolo Iacoviello, Daniela Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Via Ariosto 25 Rome 00185 Italy

Globalization, the increase of human travelling and climate changes contribute to the emergency due to arboviruses diffusion. Generally, the infected patients show only mild symptoms, but in some cases, with fragile subjects, this kind of disease can be fatal. In this paper Dengue virus is considered and described by means of a new compartmental model in which the human and the mosquitos populations interact and can infect each other;containment measures, based both on human habits and on the reduction of mosquitoes in different phase of their lives, are determined in the framework of optimal control theory, aiming at decreasing the number of infected patients and limiting the actions to be applied. This latter aspect is particularly important, both for practical and economical aspects, and for ecological reasons, since a too strong actions against mosquitos can be dangerous for the equilibrium of the ecosystem. © The Author(s) 2025.

关键词： Containment strategies Dengue virus Epidemic control Optimal control

来源：评论

学校读者我要写书评

暂无评论

Architecture of AC-DC Energy Nodes in Supergrids: A Technical Foundation for Future Renewable Integration 5

Architecture of AC-DC Energy Nodes in Supergrids: A Technica...

引用

5th National and the 1st International Conference on Applied Research in Electrical engineering, AREE 2025

作者： Mousavi, Mohammad Hossein Moradi, Hassan Rouzbehi, Kumars Razi University Department of Computer and Electrical Engineering Kermanshah Iran University of Seville Department of System Engineering and Automatic Control Seville Spain

ISBN: (纸本)9798350377170

The AC-DC Energy Nodes (ADENs) concept offers a transformative approach to modernizing power grids, particularly in the context of supergrids. By centralizing power flows from diverse renewable energy sources, such as offshore wind farms, ADENs enable efficient long-distance power transmission through HVDC technology. This design enhances the balance of supply and demand across regions and countries, significantly improving grid stability and resilience. However, the implementation of ADENs presents substantial technical, regulatory, and cybersecurity challenges. This study delves into these challenges while also addressing the geopolitical complexities of transnational connections, underscoring the critical importance of policy alignment for successful deployment. © 2025 IEEE.

关键词： Wind power integration

来源：评论

学校读者我要写书评

暂无评论

A prototype framework of design tools for computer-aided control engineering

A prototype framework of design tools for computer-aided con...

引用

IEEE International Symposium on computer Aided control System Design (CACSD)

作者： A.R. Browne J.M. Bass P.R. Croll P.J. Fleming Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK Department of Computer Science University of Sheffield Sheffield UK

This paper introduces a framework of tools which allow the design of distributed, potentially fault-tolerant, real-time control software. This framework takes a system specified in the control engineering domain and translates this application-oriented representation into a software engineering representation. From this new representation, automatic code generation tools have been developed to create a complete, executable control system implementation.< >

关键词： Prototypes control engineering computing control engineering control systems Design engineering computer aided software engineering Software engineering Software tools Automatic generation control Real time systems

来源：评论

学校读者我要写书评

暂无评论

A stacking-based model for the spread of Botryosphaeria laricina

引用

Journal of Forestry Research 2025年第1期36卷 427-443页

作者： Hongwei Zhou Shibo Zhang Meng Xie Xiaodong Li Yifan Chen Wenhao Dai College of Computer and Control Engineering Northeast Forestry UniversityHarbin 150040People’s Republic of China Key Laboratory of National Forestry and Grassland Administration On Forest and Grassland Pest Monitoring and Warning Center for Biological Disaster Prevention and ControlNational Forestry and Grassland AdministrationShenyang 110034People’s Republic of China

Botryosphaeria laricina(larch shoot blight)was first identified in 1973 in Jilin Province,*** disease spread rapidly and caused considerable damage because its pathogenesis was unknown at the time and there were no effective controls or quarantine *** present,it shows a spreading trend,but most research can only conduct physiological analyses within a relatively short period,combining individual influencing ***,methods such as neural network models,ensemble learning algorithms,and Markov models are used in pest and disease prediction and ***,there may be fitting issues or inherent limitations associated with these *** study obtained *** data at the county level from 2003 to *** dataset was augmented using the SMOTE algorithm,and then algorithms such as XGBoost were used to select the significant features from a combined set of 12 features.A new stacking fusion model has been proposed to predict the status of *** model is based on random forest,gradient boosted decision tree,CatBoost and logistic regression *** accuracy,recall,specificity,precision,F_(1) value and AUC of the model reached 90.9%,91.6%,90.4%,88.8%,90.2%and 96.2%.The results provide evidence of the strong performance and stability of the *** is mainly found in the northeast and this study indicates that it is spreading *** means should be used promptly to prevent further damage and spread.

关键词： Botryosphaeria laricina Data augmentation Feature selection Stacking Status of spread

来源：评论

学校读者我要写书评

暂无评论

Fully Distributed Model-Free Adaptive Sliding Mode control for MASs With Hybrid-Attacked Topology

引用

IEEE Transactions on Automation Science and engineering 2025年 22卷 12336-12346页

作者： Duan, Shitao Chen, Guangdeng Zhou, Qi Li, Hongyi Huang, Tingwen Guangdong University of Technology School of Automation Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control Guangdong Provincial Key Laboratory for Intelligent Decision and Cooperative Control Guangzhou510006 China Southwest University College of Electronic and Information Engineering Chongqing400715 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

A fully distributed model-free adaptive sliding mode control (MFASMC) strategy is proposed in this paper for unknown nonlinear multi-agent systems (MASs), in which topology networks are exposed to hybrid attacks consisting of denial-of-service (DoS) and false data injection attacks. Hybrid attacks in topology networks can result in neighbor information dropouts and inaccuracies among agents. First, the MASs with unknown dynamics are translated to equivalent linear data equations by the dynamic linearization technique. Second, the impact of neighbor information dropouts caused by DoS attacks is mitigated by a designed attack compensation mechanism, in which the compensation error is guaranteed to be bounded in the sense of mathematical expectation. Then, a fully distributed MFASMC algorithm, which does not depend on knowledge of the Laplacian matrix, is designed to improve the robustness of MASs with topology networks exposed to hybrid attacks, thus indirectly mitigating the impact of neighbor information inaccuracies. Finally, the consensus error is rigorously proved to be bounded in the sense of mathematical expectation, and the validity of the proposed strategy is confirmed by simulations. © 2004-2012 IEEE.

关键词： Network topology

来源：评论

学校读者我要写书评

暂无评论

DCL-depth: monocular depth estimation network based on iam and depth consistency loss

引用

Multimedia Tools and Applications 2025年第8期84卷 4773-4787页

作者： Han, Chenggong Lv, Chen Kou, Qiqi Jiang, He Cheng, Deqiang The School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China The School of Computer Science and Technology China University of Mining and Technology Xuzhou221116 China

The self-supervised monocular depth estimation algorithm obtains excellent results in outdoor environments. However, traditional self-supervised depth estimation methods often suffer from edge blurring in complex textured regions and the loss of depth information in pixels within weakly-textured areas. To enhance the perception ability of the deep network for complex textured areas and the accuracy of depth estimation in weakly-textured regions, the following methods are proposed in this paper. First of all, the image activity measure (IAM) is used to segment the image features. Based on the multi-directional distribution of image contours, the network's perception ability has been improved, resulting in effective enhancement of depth estimation in complex regions. Furthermore, a new loss function called depth consistency loss (DCL) is proposed, which is based on recursive recurrent networks. The DCL aims to measure the similarity between the output images of the first-order network and the second-order network, and the network's constraint on weak-texture regions has been strengthened. By employing this approach, the accuracy of estimating depth information in weakly-textured regions can be enhanced. Through adequate experimentation on the public indoor datasets, the results show that our network outperforms the compared algorithms in terms of accuracy and visualization of predicted depth. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Complex networks

来源：评论

学校读者我要写书评

暂无评论

DeepLeaf: an optimized deep learning approach for automated recognition of grapevine leaf diseases

引用

Neural Computing and Applications 2025年第15期37卷 8799-8823页

作者： Talaat, Fatma M. Shams, Mahmoud Y. Gamel, Samah A. ZainEldin, Hanaa Faculty of Artificial Intelligence Kafrelsheikh University Kafrelsheikh33516 Egypt Faculty of Computer Science and Engineering New Mansoura University Gamasa35712 Egypt Faculty of Engineering Horus University Damietta Egypt Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura Egypt

Plant diseases can cause severe losses in agricultural production, impacting food security and safety. Early detection of plant diseases is crucial to minimize crop damage and ensure agricultural sustainability. Manual monitoring is often impractical due to the complexity and time involved, making automated disease recognition essential. This study presents a new Plant Disease Detection Algorithm (PDDA) called DeepLeaf focused on identifying four common grapevine diseases: leaf blight, black rot, stable, and black measles. The PDDA integrates three key modules: an Image Preprocessing Module, a Feature Extraction Module, and an Optimized Convolutional Neural Network (OCNN)-based Classification Module. The OCNN forms the core of the classification system, with its hyperparameters fine-tuned using fuzzy optimization to enhance performance. Preprocessing techniques are applied to analyze diseased leaves, and a logistic regression algorithm is used to downsample the features for better analysis. The CNN is trained on images from the Plant Village dataset, allowing it to detect and classify grapevine leaf diseases accurately. The proposed model's efficiency in the automated diagnosis of grapevine diseases is demonstrated by its remarkable 99.7% accuracy rate. This high accuracy indicates that the PDDA may help with more effective and scalable plant disease monitoring, which will ultimately allow better agricultural practices. © The Author(s) 2025.

关键词： CNN Detection of leaf disease Extracting features Plant disease

来源：评论

学校读者我要写书评

暂无评论

A Data-Driven Adaptive control Approach for Enhancing the Dynamic Response of VSGs in Varying Grid Conditions

引用

IEEE Transactions on Power Delivery 2025年第3期40卷 1421-1433页

作者： Fahad, Shah She, Buxin Yin, Junjie Li, Fangxing Cui, Hantao Bo, Rui Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO USA Senior Power Systems Engineer ETAP Irvine CA USA Optimization & Control Group Parcific Northwest National Laboratory Richland USA Department of Electrical Engineering and Computer Science University of Tennessee at Knoxville Knoxville TN USA Department of Electrical and Computer Engineering North Carolina State University Raleigh NC USA

Conventionally, a virtual synchronous generator (VSG) is designed for islanded mode (IM) operation to meet specific operational requirements such as the rate of change of frequency (RoCoF). However, the operation of VSG designed for IM may not meet the operational and control criteria in grid connected mode (GCM) when the grid conditions vary. In addition, conventional VSG control technology does not consider the influence of the presynchronization scheme when connected to a weak grid, which degrades the RoCoF in IM. To overcome the aforementioned challenges, the proposed study presents a twin-delayed deep deterministic policy gradient (TD3) algorithm to improve the seamless transition performance of VSG from IM to GCM and vice versa. In the first step, the VSG-based power system model is used as a foundation for problem formulation of the proposed TD3 algorithm. Secondly, a reward function is designed according to the performance requirements, i.e., frequency and RoCoF requirements, of the VSG in order to guide the training of the agent in varying load, power reference, and grid conditions. Finally, the superiority of the proposed algorithm over existing methods is validated in MATLAB/SIMULINK and RTDS based real-time simulation environment. © 1986-2012 IEEE.

关键词： Deep reinforcement learning

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：