Automatica最新文献_第10页

Distributed model predictive control for optimal output consensus of multi-agent systems over directed graphs 有向图上多智能体系统最优输出一致性的分布式模型预测控制

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-05-22 DOI: 10.1016/j.automatica.2025.112381

Nan Bai , Qishao Wang , Zhisheng Duan , Changxin Liu

引用次数: 0

An algorithm for distributed time delay identification without a priori knowledge of the kernel 一种不需要先验核知识的分布式时延识别算法

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-05-21 DOI: 10.1016/j.automatica.2025.112382

Tobias K.S. Ritschel , John Wyller

{"title":"An algorithm for distributed time delay identification without a priori knowledge of the kernel","authors":"Tobias K.S. Ritschel , John Wyller","doi":"10.1016/j.automatica.2025.112382","DOIUrl":"10.1016/j.automatica.2025.112382","url":null,"abstract":"<div><div>Time delays are ubiquitous in industry and nature, and they significantly affect both transient dynamics and stability properties. Consequently, it is often necessary to identify and account for the delays when, e.g., designing a model-based control strategy. However, identifying delays in differential equations is not straightforward and requires specialized methods. Furthermore, existing approaches for identifying <em>distributed</em> time delays in delay differential equations (DDEs) require that the functional form of the involved kernel (also called memory function) is known. In this work, we propose an algorithm for identifying distributed delays, which does not require a priori knowledge of the kernel. Specifically, we 1) approximate the unknown kernel in the DDEs by the probability density function of a mixed Erlang distribution and 2) use the linear chain trick (LCT) to transform the resulting DDEs into ODEs. Finally, the parameters in the kernel approximation are estimated as the solution to a dynamical maximum likelihood problem, and we use a single-shooting approach to approximate this solution. We demonstrate the efficacy of the algorithm using a numerical example that involves a point reactor kinetics model of a molten salt nuclear fission reactor.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"178 ","pages":"Article 112382"},"PeriodicalIF":4.8,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144107684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Adaptive boundary control of the Kuramoto–Sivashinsky equation under intermittent sensing 间歇感知下Kuramoto-Sivashinsky方程的自适应边界控制

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-05-21 DOI: 10.1016/j.automatica.2025.112379

Mohamed Camil Belhadjoudja, Mohamed Adlene Maghenem, Emmanuel Witrant, Christophe Prieur

{"title":"Adaptive boundary control of the Kuramoto–Sivashinsky equation under intermittent sensing","authors":"Mohamed Camil Belhadjoudja, Mohamed Adlene Maghenem, Emmanuel Witrant, Christophe Prieur","doi":"10.1016/j.automatica.2025.112379","DOIUrl":"10.1016/j.automatica.2025.112379","url":null,"abstract":"<div><div>We study in this paper boundary stabilization, in the <span><math><msup><mrow><mi>L</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> sense, of the perturbed Kuramoto–Sivashinsky (KS) equation subject to intermittent sensing. We assume that we measure the state on a given spatial subdomain during certain time intervals, while we measure the state on the remaining spatial subdomain during the remaining time intervals. We assign a feedback law at the boundary of the spatial domain and force to zero the value of the state at the junction of the two subdomains. Throughout the study, the equation’s destabilizing coefficient is assumed to be unknown and possibly space dependent but bounded. As a result, adaptive boundary controllers are designed under different assumptions on the perturbation. In particular, we guarantee input-to-state stability (ISS) when an upperbound on the perturbation’s size is known. Otherwise, only global uniform ultimate boundedness (GUUB) is guaranteed. In contrast, when the state is measured at every spatial point all the time (full state measurement), convergence to an arbitrarily-small neighborhood of the origin is guaranteed, even if the perturbation’s maximal size is unknown. Numerical simulations are performed to illustrate our results.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"178 ","pages":"Article 112379"},"PeriodicalIF":4.8,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144107683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Nonlinear impulsive control for stability of dynamical systems 动态系统稳定性的非线性脉冲控制

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-05-21 DOI: 10.1016/j.automatica.2025.112371

Xiaodi Li , Ying Xing , Shiji Song

引用次数: 0

Fractional Kalman filters 分数卡尔曼滤波器

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-05-19 DOI: 10.1016/j.automatica.2025.112383

Xusheng Yang, Wen-An Zhang, Li Yu

{"title":"Fractional Kalman filters","authors":"Xusheng Yang, Wen-An Zhang, Li Yu","doi":"10.1016/j.automatica.2025.112383","DOIUrl":"10.1016/j.automatica.2025.112383","url":null,"abstract":"<div><div>The nonlinear Kalman filters usually suffer from degradation when the measurements appear in the tail of prior distribution. This article presents a new nonlinear filter named the fractional Kalman filter (FKF) for high robustness against linearization errors of both the time and the measurement updates. Based on the Bayesian theory and Gaussian assumption, an optimal fractional Gaussian filter (OFGF) is developed by maximizing the posterior PDFs, which consists of three basic steps namely time update, fractional measurement update and fractional state fusion. Specifically, the prior probability density function (PDF) and the likelihood function are factored into <span><math><mi>N</mi></math></span> parts with fractional exponents, which increases the <em>overlapping area</em> of the prior and the likelihood distributions for linearization improvement. With the OFGF and the Kullback–Leibler divergence (KLD) analysis, the FKF is developed by a deterministic sampling-based linearization for approximation of means and covariances. From the performance analysis, it reveals that the risk of destroying the stabilities of both the time update and the measurement update is reduced by introducing the fractional exponents. Finally, the effectiveness and superiority of the proposed FKF method are verified by simulations of a target tracking example.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"178 ","pages":"Article 112383"},"PeriodicalIF":4.8,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Position estimation and formation control using distance and partial state measurements 利用距离和局部状态测量进行位置估计和编队控制

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-05-19 DOI: 10.1016/j.automatica.2025.112374

Jianjun Sun , Defu Lin , Irfan Hussain , Lakmal Seneviratne , Shaoming He

{"title":"Position estimation and formation control using distance and partial state measurements","authors":"Jianjun Sun , Defu Lin , Irfan Hussain , Lakmal Seneviratne , Shaoming He","doi":"10.1016/j.automatica.2025.112374","DOIUrl":"10.1016/j.automatica.2025.112374","url":null,"abstract":"<div><div>This paper presents a distributed formation control strategy for multi-agent systems (MASs) and explores a position observer using distance measurements and partial state measurements. By leveraging infinitesimally rigid framework and matrix decomposition techniques, we pinpoint the position states that require direct measurements for satisfying local weak observability of MASs. Subsequently, by utilizing distance and partial position state measurements, we construct distributed observers to estimate positions in a global coordinate system encompassing all agents. The controller employs the gradient laws to preserve formation rigidity, facilitate collision avoidance, and ensure network connectivity. Additionally, proportional feedback is utilized to guide the agents toward desired global reference positions. Our analysis, based on the Lyapunov method, establishes the local asymptotic convergence of formation control and estimate errors, and derives lower bounds for control and observation feedback gains. To validate the effectiveness of our control method, we conduct some numerical simulations in a 3D space.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"178 ","pages":"Article 112374"},"PeriodicalIF":4.8,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 data-driven practical stabilization approach for solving stochastic dynamic programming problems 随机动态规划问题的数据驱动实用镇定方法

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-05-17 DOI: 10.1016/j.automatica.2025.112372

Massimo Tipaldi , Raffaele Iervolino , Paolo Roberto Massenio , Ali Forootani

{"title":"A data-driven practical stabilization approach for solving stochastic dynamic programming problems","authors":"Massimo Tipaldi , Raffaele Iervolino , Paolo Roberto Massenio , Ali Forootani","doi":"10.1016/j.automatica.2025.112372","DOIUrl":"10.1016/j.automatica.2025.112372","url":null,"abstract":"<div><div>This paper presents a data-driven practical stabilization approach for solving stochastic Dynamic Programming problems with unknown Markov Decision Process models over an infinite time horizon. The Bellman operator is modeled as a discrete-time switched affine system, with each mode representing a specific stationary stochastic policy and an external bounded disturbance term to account for such modeling issue. A two-step approach is followed. First, a model-based robust practical stabilization problem is solved to derive stabilization conditions which enable the practical convergence of the resulting closed-loop system trajectories towards a chosen reference value function. Then, by exploiting recent model-to-data Linear Matrix Inequality transformation tools, these results are further developed to obtain data-driven robust stabilization conditions for addressing the case of model-free problems. Such data-driven stabilization conditions are deployed into the Value Iteration algorithm, and finally tested on the recycling robot and the parking lot management problems to demonstrate the effectiveness of the proposed method.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"178 ","pages":"Article 112372"},"PeriodicalIF":4.8,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Almost sure stabilization of hybrid systems by intermittent stochastic noise with jumps 带跳跃的间歇随机噪声混合系统的几乎肯定镇定

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-05-16 DOI: 10.1016/j.automatica.2025.112373

Wei Mao , Xuerong Mao , Fuke Wu

引用次数: 0

Distributed Nash equilibrium solution for multi-agent game in adversarial environment: A reinforcement learning method 对抗环境下多智能体博弈的分布式纳什均衡解：一种强化学习方法

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-05-15 DOI: 10.1016/j.automatica.2025.112342

Qiwei Liu , Huaicheng Yan , Kaitian Chen , Meng Wang , Zhichen Li

引用次数: 0

On comparison lemmas and criteria for KL practical stability and input-to-state practical stability: the discrete-time case KL实际稳定性与输入-状态实际稳定性的比较引理与判据：离散时间情况