AutomaticaPub Date : 2025-05-22DOI: 10.1016/j.automatica.2025.112381
Nan Bai , Qishao Wang , Zhisheng Duan , Changxin Liu
{"title":"Distributed model predictive control for optimal output consensus of multi-agent systems over directed graphs","authors":"Nan Bai , Qishao Wang , Zhisheng Duan , Changxin Liu","doi":"10.1016/j.automatica.2025.112381","DOIUrl":"10.1016/j.automatica.2025.112381","url":null,"abstract":"<div><div>In this paper, a distributed model predictive control (MPC) scheme is established to solve the optimal output consensus problem of heterogeneous multi-agent systems over directed graphs. Within the framework of MPC, we take both the control input and the consistent output state as decision variables to formulate a constrained optimization problem. Inspired by the primal decomposition technique and the push-sum dual average method, a distributed algorithm is designed to address the optimization problem. The convergence analysis of the proposed algorithm is given, which shows the convergence properties related to the number of iterations. Then, considering the limited computational resources in practical applications, an improved MPC-based approach with premature termination is further developed. The closed-loop stability is analyzed under the suboptimal MPC framework, deriving appropriate terminal conditions to guarantee the asymptotic consensus of multi-agent systems. Finally, numerical simulations demonstrate the effectiveness of the theoretical results.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"178 ","pages":"Article 112381"},"PeriodicalIF":4.8,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144116383","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}
AutomaticaPub Date : 2025-05-21DOI: 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}
{"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}
AutomaticaPub Date : 2025-05-21DOI: 10.1016/j.automatica.2025.112371
Xiaodi Li , Ying Xing , Shiji Song
{"title":"Nonlinear impulsive control for stability of dynamical systems","authors":"Xiaodi Li , Ying Xing , Shiji Song","doi":"10.1016/j.automatica.2025.112371","DOIUrl":"10.1016/j.automatica.2025.112371","url":null,"abstract":"<div><div>This paper studies the stability problems for dynamical systems via nonlinear impulsive control, where the nonlinearity of the impulses is fully considered. We provide a set of Lyapunov-based sufficient conditions for local asymptotic stability (<em>LAS</em>) and the estimation of the domain of attraction, where a relationship among nonlinearity, the system structure, and impulse time sequences is established. To show the effects of nonlinearity on system performance, a novel finite-time contractive stability (<em>FTCS</em>) concept that characterizes the boundedness and finite-time contractive property of the system on the infinite domain is introduced. It shows that the nonlinearity is conducive to the stability of the system under certain conditions. Moreover, it can lead to a faster convergence speed compared to the linear case. Finally, two illustrative examples are given to verify the validity of the theoretical results.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"178 ","pages":"Article 112371"},"PeriodicalIF":4.8,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144107685","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}
AutomaticaPub Date : 2025-05-19DOI: 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}
AutomaticaPub Date : 2025-05-19DOI: 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}
AutomaticaPub Date : 2025-05-17DOI: 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}
AutomaticaPub Date : 2025-05-16DOI: 10.1016/j.automatica.2025.112373
Wei Mao , Xuerong Mao , Fuke Wu
{"title":"Almost sure stabilization of hybrid systems by intermittent stochastic noise with jumps","authors":"Wei Mao , Xuerong Mao , Fuke Wu","doi":"10.1016/j.automatica.2025.112373","DOIUrl":"10.1016/j.automatica.2025.112373","url":null,"abstract":"<div><div>This paper is concerned with the almost sure stabilization of hybrid systems by introducing intermittent stochastic noise with jumps. By means of the Lyapunov function method and the ergodic property of Markov chain, sufficient conditions are given for stability of hybrid stochastic systems with intermittent stochastic noise. With the aid of the comparison method and M-matrix theory, it is shown that hybrid systems can be stabilized by discrete-time intermittent stochastic feedback control provided the duration between two consecutive observations is sufficient small. Finally, two examples are presented to illustrate our results.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"178 ","pages":"Article 112373"},"PeriodicalIF":4.8,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071162","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}
AutomaticaPub Date : 2025-05-15DOI: 10.1016/j.automatica.2025.112342
Qiwei Liu , Huaicheng Yan , Kaitian Chen , Meng Wang , Zhichen Li
{"title":"Distributed Nash equilibrium solution for multi-agent game in adversarial environment: A reinforcement learning method","authors":"Qiwei Liu , Huaicheng Yan , Kaitian Chen , Meng Wang , Zhichen Li","doi":"10.1016/j.automatica.2025.112342","DOIUrl":"10.1016/j.automatica.2025.112342","url":null,"abstract":"<div><div>This paper investigates the leader–follower optimal consensus problem for linear multi-agent systems with adversarial inputs from a differential graphical game perspective. For the multi-agent optimal control problem described by differential graphical game, it is equally significant that the control policy is distributed and adheres to Nash equilibrium solution. However, achieving both distributed control and Nash equilibrium simultaneously has proven impossible in most existing game formulations. This paper proposes a new game formulation that can overcome this limitation, enabling each agent to reach a Nash equilibrium under a distributed policy, thereby improving system performance. Furthermore, a partially model-free reinforcement learning method is employed to obtain the optimal policy when the dynamic information is partially unknown, with admissibility condition of the initial policy further relaxed. Finally, two comparative simulations are presented to demonstrate the validity and superiority of the proposed approach.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"178 ","pages":"Article 112342"},"PeriodicalIF":4.8,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948042","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}
AutomaticaPub Date : 2025-05-15DOI: 10.1016/j.automatica.2025.112362
Pierdomenico Pepe
{"title":"On comparison lemmas and criteria for KL practical stability and input-to-state practical stability: the discrete-time case","authors":"Pierdomenico Pepe","doi":"10.1016/j.automatica.2025.112362","DOIUrl":"10.1016/j.automatica.2025.112362","url":null,"abstract":"<div><div>In this paper novel discrete-time Halanay’s inequalities are provided for the global uniform convergence to a target ball of the origin. The case with a forcing term is also studied. In this case uniform convergence is achieved towards a target ball of the origin whose radius is given by the sum of two terms: (1) a class <span><math><mi>K</mi></math></span> function of the amplitude of the forcing term; (2) a suitable constant. Induced novel criteria for global uniform ultimate boundedness and input-to-state practical stability are also provided, for a general class of nonlinear discrete-time switching systems with time delays, with possible constraints in both switching and time-delay signals.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"178 ","pages":"Article 112362"},"PeriodicalIF":4.8,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948041","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}