Automatica最新文献

{"title":"Impulsive switching signals with functional inequalities: Stability analysis using hybrid systems framework","authors":"Shenyu Liu ,&nbsp;Aneel Tanwani","doi":"10.1016/j.automatica.2024.111928","DOIUrl":"10.1016/j.automatica.2024.111928","url":null,"abstract":"<div><div>In this work, we introduce a class of impulsive switching signals described via functional inequalities which govern the switching among different modes with state resets. By choosing the parameters of the inequalities appropriately, we can recover several known classes of switching signals and also allow for signals that depend on time, mode or state of the system. Signals from this class can also be generated online via the use of an auxiliary timer while the dynamical system is running. Via a multiple Lyapunov functions approach, we provide sufficient conditions on the functional parameters of the switching signal which ensure that the equilibrium is globally asymptotically stable (GAS) for autonomous impulsive switched system. In case of inputs, similar methodology is used to provide sufficient conditions for input-to-state stability (ISS) and integral-input-to-state stability (iISS) uniformly over the proposed class of impulsive switching signals. As case studies, we consider switched systems which <em>do not</em> satisfy ISS (respectively, iISS) property for switching signals with arbitrarily large dwell-times but they are shown to be ISS (resp. iISS) for our proposed class of impulsive switchings signals described via functional inequalities.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142328028","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":"Modeling and analysis of a coupled SIS bi-virus model","authors":"Sebin Gracy ,&nbsp;Philip E. Paré ,&nbsp;Ji Liu ,&nbsp;Henrik Sandberg ,&nbsp;Carolyn L. Beck ,&nbsp;Karl Henrik Johansson ,&nbsp;Tamer Başar","doi":"10.1016/j.automatica.2024.111937","DOIUrl":"10.1016/j.automatica.2024.111937","url":null,"abstract":"<div><div>The paper deals with the setting where two viruses (say virus 1 and virus 2) coexist in a population, and they are not necessarily mutually exclusive, in the sense that infection due to one virus does not preclude the possibility of simultaneous infection due to the other. We develop a coupled bi-virus susceptible–infected–susceptible (SIS) model from a <span><math><msup><mrow><mn>4</mn></mrow><mrow><mi>n</mi></mrow></msup></math></span>-state Markov process, where <span><math><mi>n</mi></math></span> is the number of agents (i.e., individuals or subpopulation) in the population. We identify a sufficient condition for both viruses to eventually die out, and a sufficient condition for the existence, uniqueness and asymptotic stability of the endemic equilibrium of each virus. We establish a sufficient condition and multiple necessary conditions for local exponential convergence to the boundary equilibrium (i.e., one virus persists, the other one dies out) of each virus. Under mild assumptions on the healing rate, we show that there cannot exist a coexisting equilibrium where for each node there is a nonzero fraction infected only by virus 1; a nonzero fraction infected only by virus 2; but no fraction that is infected by both viruses 1 and 2. Likewise, assuming that healing rates are strictly positive, a coexisting equilibrium where for each node there is a nonzero fraction infected by both viruses 1 and 2, but no fraction is infected only by virus 1 (resp. virus 2) does not exist. Further, we provide a necessary condition for the existence of certain other kinds of coexisting equilibria. We show that, unlike the competitive bivirus model, the coupled bivirus model is not monotone. Finally, we illustrate our theoretical findings using an extensive set of simulations.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319382","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":"Reduced-order energy shaping control of large-scale linear port-Hamiltonian systems","authors":"Cristobal Ponce ,&nbsp;Hector Ramirez ,&nbsp;Yann Le Gorrec","doi":"10.1016/j.automatica.2024.111934","DOIUrl":"10.1016/j.automatica.2024.111934","url":null,"abstract":"<div><div>This paper is concerned with reduced-order control design for a class of high dimensional linear port-Hamiltonian systems stemming from the modeling of large-scale systems networks or from the discretization of distributed parameter systems. A class of dynamic controllers synthesized from low-dimensional and reduced-order models of the system are proposed. First, the controller structure and the criteria for asymptotic stability are established for a controller based on the full-order model. Then, using structural invariants, two design methods are proposed and compared: one based on a low-dimensional model of the system and the other on a reduced-order model based on modal truncation. With applications in shape control in mind, the system’s equilibrium points are parametrized using the controller parameters. It allows to establish an optimal criterion to minimize the norm of the error between the intended and achievable closed-loop equilibrium configurations. An asymptotic stability margin in terms of the full and low/reduced order models stiffness matrices is provided and related with the closed-loop transient performances. Mindlin plate with specific inputs is used to show how dynamic shape control can be achieved using the proposed approach.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319383","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":"Linear formation control of multi-agent systems","authors":"Xiaozhen Zhang ,&nbsp;Qingkai Yang ,&nbsp;Fan Xiao ,&nbsp;Hao Fang ,&nbsp;Jie Chen","doi":"10.1016/j.automatica.2024.111935","DOIUrl":"10.1016/j.automatica.2024.111935","url":null,"abstract":"<div><div>This paper proposes a new distributed leader–follower control architecture, termed linear formation control, to realize formation variations. The objective is to navigate a group of agents to reach a specific target formation, which is a linear transformation of the pre-defined nominal configuration, whose dimension can be higher than agents’ coordinates. The proposed architecture enables the formation to adjust through arbitrary linear transformations to accommodate the environment, offering a diverse range of feasible formations. First, we introduce the concept of “linear localizability” that leaders can uniquely determine the target formation. Then, using the pre-defined stress matrix, we propose a linear formation control method, which can be regarded as an extension of recent affine formation control approaches. Next, in the situation where the stress matrix is unavailable, distributed estimators are designed to obtain accurate linear formation parameters. We propose an estimation-driven linear formation control method using the graph Laplacian matrix. Finally, simulations are conducted to verify the effectiveness of the proposed linear formation control schemes.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319381","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":"Privacy-preserving nonlinear cloud-based model predictive control via affine masking","authors":"Kaixiang Zhang ,&nbsp;Zhaojian Li ,&nbsp;Yongqiang Wang ,&nbsp;Nan Li","doi":"10.1016/j.automatica.2024.111939","DOIUrl":"10.1016/j.automatica.2024.111939","url":null,"abstract":"<div><div>With the advent of 5G technology that presents enhanced communication reliability and ultra-low latency, there is renewed interest in employing cloud computing to perform high performance but computationally expensive control schemes like nonlinear model predictive control (MPC). Such a cloud-based control scheme, however, requires data sharing between the plant (agent) and the cloud, which raises privacy concerns. This is because privacy-sensitive information such as system states and control inputs has to be sent to/from the cloud and thus can be leaked to attackers for various malicious activities. In this paper, we develop a simple yet effective affine masking strategy for privacy-preserving nonlinear MPC. Specifically, we consider external eavesdroppers or honest-but-curious cloud servers that wiretap the communication channel and intend to infer the plant’s information including state information and control inputs. An affine transformation-based privacy-preservation mechanism is designed to mask the true states and control signals while reformulating the original MPC problem into a different but equivalent form. We show that the proposed privacy scheme does not affect the MPC performance and it preserves the privacy of the plant such that the eavesdropper is unable to identify the actual value or even estimate a rough range of the private state and input signals. The proposed method is further extended to achieve privacy preservation in cloud-based output-feedback MPC. Simulations are performed to demonstrate the efficacy of the developed approaches.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0005109824004333/pdfft?md5=84e1c2afaefd4d14ab609e6faa1f5a7f&pid=1-s2.0-S0005109824004333-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

{"title":"Further results on fixed-time control for nonlinear systems with asymmetric output constraints","authors":"Huifang Min ,&nbsp;Shang Shi ,&nbsp;Jason Gu ,&nbsp;Na Duan","doi":"10.1016/j.automatica.2024.111933","DOIUrl":"10.1016/j.automatica.2024.111933","url":null,"abstract":"<div><div>This paper concerns the fixed-time control with an arbitrarily prescribed upper bound of settling-time (UBST) for nonlinear systems with asymmetric output constraints. We introduce a novel time-varying gain function that effectively addresses the issue of infinite-gain, which has been a challenge in related research. By utilizing this gain function, we present two theorems that employ the Lyapunov function for constrained nonlinear systems. These theorems serve as guidelines for constructing controllers without violation of constraints. In addition, a novel barrier Lyapunov function (BLF) is exploited which is equivalent to the classical one for nonlinear systems without constraints. By using the proposed theorems, BLF and fixed-time backstepping design procedure, a state-feedback controller is constructed and analyzed for output-constrained nonlinear systems. It is proved that the designed controller can render the closed-loop system converges to the origin within a fixed settling time while maintaining at the origin thereafter, the controller is uniformly bounded and the output constraints are not violated. Finally, simulations and comparisons are provided to verify the proposed control schemes.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0005109824004278/pdfft?md5=865255b5af5e705c2cca0a9f80a48a54&pid=1-s2.0-S0005109824004278-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

{"title":"Modelling of memristor networks and the effective memristor","authors":"Anne-Men Huijzer,&nbsp;Arjan van der Schaft,&nbsp;Bart Besselink","doi":"10.1016/j.automatica.2024.111922","DOIUrl":"10.1016/j.automatica.2024.111922","url":null,"abstract":"<div><p>This paper presents a mathematical framework for the modelling and analysis of networks of memristors, where we describe a memristor as a monotone relation between electric charge and magnetic flux. Using this framework, we show that the port behaviour of networks of monotone memristors can equivalently be described by a single monotone memristor, the so-called effective memristor. The behaviour of the effective memristor is influenced by the monotonicity properties of the single memristors and the structure of the network of memristors. An algorithm is provided to derive an explicit characterisation of the effective memristor of any network of memristors. In addition, explicit bounds on the effective memristance curve are derived in terms of the effective resistance of associated resistor networks. Finally, an explicit description of the port behaviour of series and parallel interconnections is derived and simulation examples are provided for two simple circuits.</p></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0005109824004163/pdfft?md5=5954be949d5faa6ab8a4d214958bffed&pid=1-s2.0-S0005109824004163-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

{"title":"Equi-normalized robust positively invariant sets for linear difference inclusions","authors":"Saša V. Raković ,&nbsp;Paul Trodden","doi":"10.1016/j.automatica.2024.111930","DOIUrl":"10.1016/j.automatica.2024.111930","url":null,"abstract":"<div><p>This note establishes the characterization, existence and uniqueness of equi-normalized polytopic robust positively invariant sets for linear difference inclusions. The computation of this set results in a nonconvex optimization problem. Although this may be reformulated exactly as a mixed integer linear programme, we propose a more practical and tractable alternative in the form of a fixed-point iteration based on linear programming. Convergence of the algorithm is established.</p></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0005109824004242/pdfft?md5=296bd675522f3c88e6856b48384e7426&pid=1-s2.0-S0005109824004242-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

{"title":"Deep networks for system identification: A survey","authors":"Gianluigi Pillonetto ,&nbsp;Aleksandr Aravkin ,&nbsp;Daniel Gedon ,&nbsp;Lennart Ljung ,&nbsp;Antônio H. Ribeiro ,&nbsp;Thomas B. Schön","doi":"10.1016/j.automatica.2024.111907","DOIUrl":"10.1016/j.automatica.2024.111907","url":null,"abstract":"<div><p>Deep learning is a topic of considerable current interest. The availability of massive data collections and powerful software resources has led to an impressive amount of results in many application areas that reveal essential but hidden properties of the observations. System identification learns mathematical descriptions of dynamic systems from input–output data and can thus benefit from the advances of deep neural networks to enrich the possible range of models to choose from. For this reason, we provide a survey of deep learning from a system identification perspective. We cover a wide spectrum of topics to enable researchers to understand the methods, providing rigorous practical and theoretical insights into the benefits and challenges of using them. The main aim of the identified model is to predict new data from previous observations. This can be achieved with different deep learning-based modelling techniques and we discuss architectures commonly adopted in the literature, like feedforward, convolutional, and recurrent networks. Their parameters have to be estimated from past data to optimize the prediction performance. For this purpose, we discuss a specific set of first-order optimization tools that have emerged as efficient. The survey then draws connections to the well-studied area of kernel-based methods. They control the data fit by regularization terms that penalize models not in line with prior assumptions. We illustrate how to cast them in deep architectures to obtain deep kernel-based methods. The success of deep learning also resulted in surprising empirical observations, like the counter-intuitive behaviour of models with many parameters. We discuss the role of overparameterized models, including their connection to kernels, as well as implicit regularization mechanisms which affect generalization, specifically the interesting phenomena of benign overfitting and double-descent. Finally, we highlight numerical, computational and software aspects in the area with the help of applied examples.</p></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0005109824004011/pdfft?md5=369128fac8aa3dbd37df831300f34a92&pid=1-s2.0-S0005109824004011-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}

{"title":"Performance optimization for continuous network localization","authors":"Liangming Chen ,&nbsp;Chenyang Liang ,&nbsp;Yibei Li ,&nbsp;Jie Mei ,&nbsp;Lihua Xie","doi":"10.1016/j.automatica.2024.111903","DOIUrl":"10.1016/j.automatica.2024.111903","url":null,"abstract":"<div><div>Recent advances in linear localization of sensor networks allow sensors to localize themselves by using inter-sensor measurements, such as distances, bearings and interior angles. According to earlier works, linear localization algorithms’ performance is relatively poor, which, however, has not been adequately addressed in the existing literature. The aim of this paper is to improve the performance of linear and continuous localization algorithms. More specifically, we focus on improving three key aspects of linear localization algorithms’ performance, i.e., the stability margin, convergence rate and robustness against measurement noises. Firstly, we propose a unified description for networks’ linear localization algorithms, given different types of measurements, and show that the stability margin, convergence rate and robustness of linear localization algorithms are <em>commonly determined by one parameter</em>, namely, <em>the minimum eigenvalue of the network’s localization matrix</em>. Secondly, by carefully choosing the decision variable, we formulate the performance optimization problem as an eigenvalue optimization problem, and show the non-differentiability of the eigenvalue optimization problem. Thirdly, we propose a <em>distributed</em> optimization algorithm, which guarantees the convergence to an optimal solution of the eigenvalue optimization problem. Finally, simulation examples validate the effectiveness of the proposed distributed optimization algorithm.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0005109824003972/pdfft?md5=b83e4f85681639649512cbb0fd10cf71&pid=1-s2.0-S0005109824003972-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}