IEEE Systems Journal最新文献_第9页

ELISE: A Reinforcement Learning Framework to Optimize the Slotframe Size of the TSCH Protocol in IoT Networks ELISE：优化物联网网络中 TSCH 协议槽框大小的强化学习框架

IF 4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-03-18 DOI: 10.1109/JSYST.2024.3371429

F. Fernando Jurado-Lasso;Mohammadreza Barzegaran;J. F. Jurado;Xenofon Fafoutis

{"title":"ELISE: A Reinforcement Learning Framework to Optimize the Slotframe Size of the TSCH Protocol in IoT Networks","authors":"F. Fernando Jurado-Lasso;Mohammadreza Barzegaran;J. F. Jurado;Xenofon Fafoutis","doi":"10.1109/JSYST.2024.3371429","DOIUrl":"10.1109/JSYST.2024.3371429","url":null,"abstract":"The Internet of Things is shaping the next generation of cyber–physical systems to improve the future industry for smart cities. It has created novel and essential applications that require specific network performance to enhance the quality of services. Since network performance requirements are application-oriented, it is of paramount importance to provide tailored solutions that seamlessly manage the network resources and orchestrate the network to satisfy user requirements. In this article, we propose ELISE, a reinforcement learning (RL) framework to optimize the slotframe size of the time slotted channel hopping protocol in IIoT networks while considering the user requirements. We primarily address the problem of designing a framework that self-adapts to the optimal slotframe length that best suits the user's requirements. The framework takes care of all functionalities involved in the correct functioning of the network, while the RL agent instructs the framework with a set of actions to determine the optimal slotframe size each time the user requirements change. We evaluate the performance of ELISE through extensive analysis based on simulations and experimental evaluations on a testbed to demonstrate the efficiency of the proposed approach in adapting network resources at runtime to satisfy user requirements.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"1068-1079"},"PeriodicalIF":4.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10473707","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140168118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE Systems Journal Publication Information IEEE 系统期刊出版信息

IF 4.4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-03-18 DOI: 10.1109/JSYST.2024.3363070

引用次数: 0

IEEE Systems Council Information 电气和电子工程师学会系统理事会信息

IF 4.4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-03-18 DOI: 10.1109/JSYST.2024.3363066

引用次数: 0

Learning-Based Virtual Inertia Control of an Islanded Microgrid With High Participation of Renewable Energy Resources 可再生能源高度参与的孤岛式微电网基于学习的虚拟惯性控制

IF 4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-03-18 DOI: 10.1109/JSYST.2024.3370655

Mohammad Hossein Norouzi;Arman Oshnoei;Behnam Mohammadi-Ivatloo;Mehdi Abapour

{"title":"Learning-Based Virtual Inertia Control of an Islanded Microgrid With High Participation of Renewable Energy Resources","authors":"Mohammad Hossein Norouzi;Arman Oshnoei;Behnam Mohammadi-Ivatloo;Mehdi Abapour","doi":"10.1109/JSYST.2024.3370655","DOIUrl":"10.1109/JSYST.2024.3370655","url":null,"abstract":"Renewable energy sources (RESs) are increasingly used to meet consumer demands in microgrids (MGs). However, high RES integration introduces system frequency stability, inertia, and damping reduction challenges. Virtual inertia (VI) control has been recognized as an effective solution to improve system frequency response in such circumstances. Conventional control techniques for VI control, which rely heavily on specific operating conditions, can lead to flawed performance during contingencies due to their lack of adaptivity. To address these challenges, this article proposes a novel attitude found on brain emotional learning (BEL) to emulate VI and damping for effective frequency control. The BEL-based controller is capable of quickly learning and handling the complexity, nonlinearity, and uncertainty intrinsic to the MGs, and it operates independently of prior knowledge of the system model and parameters. This characteristic enables the controller to adapt to various operating conditions, improving its robustness. The simulation results across three disturbance scenarios show that the proposed BEL-based controller significantly improves the system's response. The absolute maximum deviation of frequency was reduced to 0.0561 Hz in the final scenario, marking performance enhancements of 46.62% and 49.04% when compared with the artificial neural network-based proportional–integral control and the standard proportional control, respectively. This underlines the controller's adaptability and superior effectiveness in varying operating conditions.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"786-795"},"PeriodicalIF":4.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140168347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE Systems Journal Information for Authors IEEE 系统期刊作者信息

IF 4.4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-03-18 DOI: 10.1109/JSYST.2024.3363064

引用次数: 0

List of Reviewers 审查员名单

IF 4.4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-03-18 DOI: 10.1109/JSYST.2024.3363588

引用次数: 0

Fixed-Time Hierarchical Distributed Control for Flexible Thermostatically Controlled Loads 灵活恒温负载的固定时间分层分布式控制

IF 4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-03-18 DOI: 10.1109/JSYST.2024.3366226

Zilong Mi;Zhengmin Kong;Tao Huang;Peng Shi;Zhenwei Yu;Li Ding

{"title":"Fixed-Time Hierarchical Distributed Control for Flexible Thermostatically Controlled Loads","authors":"Zilong Mi;Zhengmin Kong;Tao Huang;Peng Shi;Zhenwei Yu;Li Ding","doi":"10.1109/JSYST.2024.3366226","DOIUrl":"10.1109/JSYST.2024.3366226","url":null,"abstract":"With the growing integration of unpredictable renewable energy sources into the grid, achieving power balance has become an increasingly crucial challenge. To address this challenge, demand response has emerged as a promising solution. This article proposes a new demand-side flexible thermostatically controlled loads response strategy framework. Our method employs a hierarchical control framework that covers three layers of control, which consist of the optimization layer, coordination layer, and local control layer. The optimization layer employs a dynamic average consensus algorithm for economic optimization scheduling to maximize the sum of the aggregators' welfare functions. In the coordination layer, power is distributed fairly based on the comfort state, generating reference signals for the local control layer. The local control layer tracks these reference signals and employs integral sliding mode control to suppress the influence of unknown disturbances. The control objectives of the entire framework can be achieved in a fixed time, and the parameters in the framework are heterogeneous. Furthermore, the relationships between controller parameters and tracking performance are derived, and the upper bounds of settling time are estimated. Finally, we demonstrate the validity of our theoretical results through numerical simulations.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"1344-1355"},"PeriodicalIF":4.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140168236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bipartite Leader-Following Consensus of Nonlinear Switched Multiagent Systems Under Model-Depended Dynamic Event-Triggered Control 模型依赖动态事件触发控制下非线性开关多代理系统的两方领导-跟随共识

IF 4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-03-17 DOI: 10.1109/JSYST.2024.3397301

Shuo Zhang;Jinhai Liu;Wei Wang;Zhigang Zhang

引用次数: 0

Enhanced-Interval Optimal Scheduling of Power-Transportation Interconnected System Considering Pile (Station) Equilibrium Price 考虑桩（站）平衡价格的电力-交通互联系统增强型间隔优化调度

IF 4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-03-17 DOI: 10.1109/JSYST.2024.3398049

Min Hou;Xinrui Liu;Rui Wang;Chaoyu Dong;Qiuye Sun

{"title":"Enhanced-Interval Optimal Scheduling of Power-Transportation Interconnected System Considering Pile (Station) Equilibrium Price","authors":"Min Hou;Xinrui Liu;Rui Wang;Chaoyu Dong;Qiuye Sun","doi":"10.1109/JSYST.2024.3398049","DOIUrl":"10.1109/JSYST.2024.3398049","url":null,"abstract":"As the distribution network is affected by the high proportion of renewable energy connected to the grid and the disorderly charging of electric vehicles, how to formulate the optimal scheduling strategy to ensure the safety and stability of the system has become an urgent problem to be solved. Aiming at the uncertainty of the user behavior of the traffic network, a charging pile (station) pricing strategy based on stochastic user equilibrium (SUE) is proposed. The equilibrium electricity price of charging pile (station) is formulated to guide the traffic flow and realize the collaborative optimization of the distribution network. Considering the traffic congestion caused by user behavior, a congestion charging policy is proposed to promote static hybrid SUE. Its feasibility is proved by Karush-Kuhn-Tucker (KKT) condition and variational inequality. In addition, through the introduction of joint pricing center, charging pile (station) electricity price, and congestion charging policy are proposed. Aiming at the uncertainty of system, an enhanced-interval optimal method is established. Finally, the simulation analysis of the power-transportation interconnected system verifies that the congestion charging policy can optimize the unit output, and the enhanced-interval optimal method can solve the uncertain influence, reduce the system cost, and ensure the satisfaction of traffic users.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"1320-1331"},"PeriodicalIF":4.0,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141058599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Rate-Splitting Strategy for STAR-RIS-Aided Massive MIMO Systems With Joint Optimization 联合优化 STAR-RIS 辅助大规模多输入多输出系统的速率分配策略

IF 4 3区计算机科学

IEEE Systems Journal Pub Date : 2024-03-16 DOI: 10.1109/JSYST.2024.3398249

Hanxiao Ge;Anastasios Papazafeiropoulos;Navneet Garg;Tharmalingam Ratnarajah

{"title":"A Rate-Splitting Strategy for STAR-RIS-Aided Massive MIMO Systems With Joint Optimization","authors":"Hanxiao Ge;Anastasios Papazafeiropoulos;Navneet Garg;Tharmalingam Ratnarajah","doi":"10.1109/JSYST.2024.3398249","DOIUrl":"10.1109/JSYST.2024.3398249","url":null,"abstract":"This work proposes a rate-splitting (RS) strategy for simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) aided massive multiple-input multiple-output (mMIMO) systems to reduce the interference among multiple users and enhance the spectral efficiency (SE) while improving the coverage degraded by blockages. Specifically, we use the RS to design the precoder for the common part by solving the asymptotic problem. Also, unlike traditional RIS-aided systems, receivers can be positioned on either side of the RIS panel in the proposed system. We derive the sum-rate based on statistical channel state information (CSI) to reduce the signal overhead. Next, we optimize the rate through a projected gradient ascent method algorithm simultaneously with respect to the amplitudes and phase shifts of the STAR-RIS. Simulations show the advantages of the RS strategy compared with the broadcasting strategy in improving the sum-rate. We further evaluate the efficiency of the STAR-RIS system against the traditional RIS-aided system. In our analysis, we employ energy splitting and mode switching protocols to fine-tune the transmission and reflection coefficients of the outgoing and incoming signals.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"977-988"},"PeriodicalIF":4.0,"publicationDate":"2024-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141058658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0