IEEE Control Systems Letters最新文献_第3页

Impact of Opinion on Disease Transmission With Waterborne Pathogen and Stubborn Community 水传播病原体和顽固群落对疾病传播的影响

IF 2.4

IEEE Control Systems Letters Pub Date : 2024-10-24 DOI: 10.1109/LCSYS.2024.3485963

Qingsong Liu;Li Ma

引用次数: 0

Numerical and Lyapunov-Based Investigation of the Effect of Stenosis on Blood Transport Stability Using a Control-Theoretic PDE Model of Cardiovascular Flow 利用心血管流动的控制论 PDE 模型，基于数值和 Lyapunov 对狭窄对血液运输稳定性影响的研究

IF 2.4

IEEE Control Systems Letters Pub Date : 2024-10-23 DOI: 10.1109/LCSYS.2024.3484635

Shantanu Singh;Nikolaos Bekiaris-Liberis

{"title":"Numerical and Lyapunov-Based Investigation of the Effect of Stenosis on Blood Transport Stability Using a Control-Theoretic PDE Model of Cardiovascular Flow","authors":"Shantanu Singh;Nikolaos Bekiaris-Liberis","doi":"10.1109/LCSYS.2024.3484635","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3484635","url":null,"abstract":"We perform various numerical tests to study the effect of (boundary) stenosis on blood flow stability, employing a detailed and accurate, second-order finite-volume scheme for numerically implementing a partial differential equation (PDE) model, using clinically realistic values for the artery’s parameters and the blood inflow. The model consists of a baseline \u0000<inline-formula> <tex-math>$2times 2$ </tex-math></inline-formula>\u0000 hetero-directional, nonlinear hyperbolic PDE system, in which, the stenosis’ effect is described by a pressure drop at the outlet of an arterial segment considered. We then study the stability properties (observed in our numerical tests) of a reference trajectory, corresponding to a given time-varying inflow (e.g., a periodic trajectory with period equal to the time interval between two consecutive heartbeats) and stenosis severity, deriving the respective linearized system and constructing a Lyapunov functional. Due to the fact that the linearized system is time varying, with time-varying parameters depending on the reference trajectories themselves (that, in turn, depend in an implicit manner on the stenosis degree), which cannot be derived analytically, we verify the Lyapunov-based stability conditions obtained, numerically. Both the numerical tests and the Lyapunov-based stability analysis show that a reference trajectory is asymptotically stable with a decay rate that decreases as the stenosis severity deteriorates.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"2403-2408"},"PeriodicalIF":2.4,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Higher-Order Non-Autonomous Optimal Area Coverage Control 高阶非自主优化区域覆盖控制

IF 2.4

IEEE Control Systems Letters Pub Date : 2024-10-18 DOI: 10.1109/LCSYS.2024.3483668

Qianyu Li;Davide Spinello

引用次数: 0

Almost Sure Convergence and Non-Asymptotic Concentration Bounds for Stochastic Mirror Descent Algorithm 随机镜像后裔算法的几乎确定收敛性和非渐近集中限界

IF 2.4

IEEE Control Systems Letters Pub Date : 2024-10-16 DOI: 10.1109/LCSYS.2024.3482148

Anik Kumar Paul;Arun D. Mahindrakar;Rachel K. Kalaimani

引用次数: 0

Opinion Dynamics With Set-Based Confidence: Convergence Criteria and Periodic Solutions 基于集合信心的意见动态：收敛标准和周期性解决方案

IF 2.4

IEEE Control Systems Letters Pub Date : 2024-10-14 DOI: 10.1109/LCSYS.2024.3479275

Iryna Zabarianska;Anton V. Proskurnikov

{"title":"Opinion Dynamics With Set-Based Confidence: Convergence Criteria and Periodic Solutions","authors":"Iryna Zabarianska;Anton V. Proskurnikov","doi":"10.1109/LCSYS.2024.3479275","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3479275","url":null,"abstract":"This letter introduces a new multidimensional extension of the Hegselmann-Krause (HK) opinion dynamics model, where opinion proximity is not determined by a norm or metric. Instead, each agent trusts opinions within the Minkowski sum \u0000<inline-formula> <tex-math>$boldsymbol {xi }+boldsymbol {mathcal {O}}$ </tex-math></inline-formula>\u0000, where \u0000<inline-formula> <tex-math>$boldsymbol {xi }$ </tex-math></inline-formula>\u0000 is the agent’s current opinion and \u0000<inline-formula> <tex-math>$boldsymbol {mathcal {O}}$ </tex-math></inline-formula>\u0000 is the confidence set defining acceptable deviations. During each iteration, agents update their opinions by simultaneously averaging the trusted opinions. Unlike traditional HK systems, where \u0000<inline-formula> <tex-math>$boldsymbol {mathcal {O}}$ </tex-math></inline-formula>\u0000 is a ball in some norm, our model allows the confidence set to be non-convex and even unbounded. The new model, referred to as SCOD (Set-based Confidence Opinion Dynamics), can exhibit properties absent in the conventional HK model. Some solutions may converge to non-equilibrium points in the state space, while others oscillate periodically. These “pathologies” disappear if the set \u0000<inline-formula> <tex-math>$boldsymbol {mathcal {O}}$ </tex-math></inline-formula>\u0000 is symmetric and contains zero in its interior: similar to the usual HK model, the SCOD then converge in a finite number of iterations to one of the equilibrium points. The latter property is also preserved if one agent is “stubborn” and resists changing their opinion, yet still influences the others; however, two stubborn agents can lead to oscillations.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"2373-2378"},"PeriodicalIF":2.4,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10715999","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142552002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Computation and Formal Verification of Neural Network Contraction Metrics 神经网络收缩指标的计算与形式验证

IF 2.4

IEEE Control Systems Letters Pub Date : 2024-10-11 DOI: 10.1109/LCSYS.2024.3478272

Maxwell Fitzsimmons;Jun Liu

引用次数: 0

Pointwise-Sparse Actuator Scheduling for Linear Systems With Controllability Guarantee 具有可控性保证的线性系统的点状稀疏执行器调度

IF 2.4

IEEE Control Systems Letters Pub Date : 2024-10-07 DOI: 10.1109/LCSYS.2024.3475886

Luca Ballotta;Geethu Joseph;Irawati Rahul Thete

引用次数: 0

Negativizability for Nonlinear Estimation in Cyber–Physical Systems 网络物理系统中非线性估计的可否定性

IF 2.4

IEEE Control Systems Letters Pub Date : 2024-10-07 DOI: 10.1109/LCSYS.2024.3473789

Camilla Fioravanti;Stefano Panzieri;Gabriele Oliva

引用次数: 0

The Design of ϵ-Optimal Strategy for Two-Person Zero-Sum Markov Games 两人零和马尔可夫博弈的ϵ-最优策略设计

IF 2.4

IEEE Control Systems Letters Pub Date : 2024-10-04 DOI: 10.1109/LCSYS.2024.3474057

Kaiyun Xie;Junlin Xiong

{"title":"The Design of ϵ-Optimal Strategy for Two-Person Zero-Sum Markov Games","authors":"Kaiyun Xie;Junlin Xiong","doi":"10.1109/LCSYS.2024.3474057","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3474057","url":null,"abstract":"This letter focuses on designing approximate Nash strategies for the two-person zero-sum Markov game. Using the receding horizon method, the \u0000<inline-formula> <tex-math>$epsilon $ </tex-math></inline-formula>\u0000-optimal strategies are designed to approximate Nash strategies by executing finite Gauss-Seidel iterations. The relationship between the approximation value of \u0000<inline-formula> <tex-math>$epsilon $ </tex-math></inline-formula>\u0000 and the number of iterations is also analyzed. Additionally, the \u0000<inline-formula> <tex-math>$epsilon $ </tex-math></inline-formula>\u0000-optimal strategies are designed for two scenarios with imprecise parameters. For scenarios with imprecise values, the value of \u0000<inline-formula> <tex-math>$epsilon $ </tex-math></inline-formula>\u0000 is determined based on the errors between imprecise and iteration values. It provides a theoretical basis for efficiently designing \u0000<inline-formula> <tex-math>$epsilon $ </tex-math></inline-formula>\u0000-optimal strategies using heuristic algorithms or approximate dynamic programming. For scenarios with imprecise transition probabilities, the value of \u0000<inline-formula> <tex-math>$epsilon $ </tex-math></inline-formula>\u0000 is determined based on the errors between the estimated and practical transition probabilities. It enables the use of pattern recognition technology or other methods to estimate practical transition probabilities for designing \u0000<inline-formula> <tex-math>$epsilon $ </tex-math></inline-formula>\u0000-optimal strategies.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"2349-2354"},"PeriodicalIF":2.4,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Detecting Stubborn Behaviors in Influence Networks: A Model-Based Approach for Resilient Analysis 检测影响网络中的顽固行为：基于模型的弹性分析方法

IF 2.4

IEEE Control Systems Letters Pub Date : 2024-10-01 DOI: 10.1109/LCSYS.2024.3472495

Roberta Raineri;Chiara Ravazzi;Giacomo Como;Fabio Fagnani

{"title":"Detecting Stubborn Behaviors in Influence Networks: A Model-Based Approach for Resilient Analysis","authors":"Roberta Raineri;Chiara Ravazzi;Giacomo Como;Fabio Fagnani","doi":"10.1109/LCSYS.2024.3472495","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3472495","url":null,"abstract":"The wide spread of on-line social networks poses new challenges in information environment and cybersecurity. A key issue is detecting stubborn behaviors to identify leaders and influencers for marketing purposes, or extremists and automatic bots as potential threats. Existing literature typically relies on known network topology and extensive centrality measures computation. However, the size of social networks and their often unknown structure could make social influence computation impractical. We propose a new approach based on opinion dynamics to estimate stubborn agents from data. We consider a DeGroot model in which regular agents adjust their opinions as a linear combination of their neighbors’ opinions, whereas stubborn agents keep their opinions constant over time. We formulate the stubborn nodes identification and their influence estimation problems as a low-rank approximation problem. We then propose an interpolative decomposition algorithm for their solution. We determine sufficient conditions on the model parameters to ensure the algorithm’s resilience to noisy observations. Finally, we corroborate our theoretical analysis through numerical results.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"2343-2348"},"PeriodicalIF":2.4,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0