Annual Reviews in Control最新文献_第10页

A classification of cybersecurity strategies in the context of Discrete Event Systems 离散事件系统背景下的网络安全策略分类

IF 9.4 2区计算机科学

Annual Reviews in Control Pub Date : 2023-01-01 DOI: 10.1016/j.arcontrol.2023.100907

Samuel Oliveira , André B. Leal , Marcelo Teixeira , Yuri K. Lopes

{"title":"A classification of cybersecurity strategies in the context of Discrete Event Systems","authors":"Samuel Oliveira , André B. Leal , Marcelo Teixeira , Yuri K. Lopes","doi":"10.1016/j.arcontrol.2023.100907","DOIUrl":"https://doi.org/10.1016/j.arcontrol.2023.100907","url":null,"abstract":"<div><p>In recent years, cybersecurity has received increasing attention due to the demand from a large class of networked systems for resilience against cyberattacks that may compromise privacy, integrity and availability. Many of these systems are abstracted as Discrete Event Systems (DES) as their evolution occurs through the occurrence of discrete events. Since they use communication networks and consequently may be vulnerable to attacks, cybersecurity must be considered in DES. Based on this challenging scenario, this work focuses on cybersecurity strategies in the context of DES. A systematic literature mapping (SLM) was carried out, which selected 208 papers on the aforementioned topic. These papers were analyzed and categorized regarding the characteristics of each cybersecurity strategy, the types of attacks considered and also the modeling formalism used. The primary objective of this work is to collect all relevant research in the literature to provide the state of the art on cybersecurity strategies for DES, as well as identify research trends and directions for future work on the topic. The results show that the majority of the selected papers present cybersecurity methods based on the strategy of protecting systems against passive attacks, using automata as the modeling formalism. In contrast, the topic of active attacks has gained attention in recent years, with an increasing number of papers published in several journals and conferences. Finally, research gaps and challenges are presented to provide future directions in the domain of the cybersecurity of DES.</p></div>","PeriodicalId":50750,"journal":{"name":"Annual Reviews in Control","volume":"56 ","pages":"Article 100907"},"PeriodicalIF":9.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49740203","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

Composite adaptation and learning for robot control: A survey 机器人控制的复合自适应与学习研究综述

IF 9.4 2区计算机科学

Annual Reviews in Control Pub Date : 2023-01-01 DOI: 10.1016/j.arcontrol.2022.12.001

Kai Guo , Yongping Pan

{"title":"Composite adaptation and learning for robot control: A survey","authors":"Kai Guo , Yongping Pan","doi":"10.1016/j.arcontrol.2022.12.001","DOIUrl":"https://doi.org/10.1016/j.arcontrol.2022.12.001","url":null,"abstract":"<div><p>Composite adaptation and learning techniques were initially proposed for improving parameter convergence in adaptive control and have generated considerable research interest in the last three decades, inspiring numerous robot control applications. The key idea is that more sources of parametric information are applied to drive parameter estimates aside from trajectory tracking errors. Both composite adaptation and learning can ensure superior stability and performance. However, composite learning possesses a unique feature in that online data memory is fully exploited to extract parametric information such that parameter convergence can be achieved without a stringent condition termed persistent excitation. In this article, we provide the first systematic and comprehensive survey of prevalent composite adaptation and learning approaches for robot control, especially focusing on exponential parameter convergence. Composite adaptation is classified into regressor-filtering composite adaptation and error-filtering composite adaptation, and composite learning is classified into discrete-data regressor extension and continuous-data regressor extension. For the sake of clear presentation and better understanding, a general class of robotic systems is applied as a unifying framework to show the motivation, synthesis, and characteristics of each parameter estimation method for adaptive robot control. The strengths and deficiencies of all these methods are also discussed sufficiently. We have concluded by suggesting possible directions for future research in this area.</p></div>","PeriodicalId":50750,"journal":{"name":"Annual Reviews in Control","volume":"55 ","pages":"Pages 279-290"},"PeriodicalIF":9.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49762796","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: 5

On the variable structure control approach with sliding modes to robust finite-time consensus problems: A methodological overview based on nonsmooth analysis 鲁棒有限时间一致问题的滑模变结构控制方法:基于非光滑分析的方法综述

IF 9.4 2区计算机科学

Annual Reviews in Control Pub Date : 2023-01-01 DOI: 10.1016/j.arcontrol.2023.04.002

A. Pilloni, M. Franceschelli, A. Pisano, E. Usai

{"title":"On the variable structure control approach with sliding modes to robust finite-time consensus problems: A methodological overview based on nonsmooth analysis","authors":"A. Pilloni, M. Franceschelli, A. Pisano, E. Usai","doi":"10.1016/j.arcontrol.2023.04.002","DOIUrl":"https://doi.org/10.1016/j.arcontrol.2023.04.002","url":null,"abstract":"<div><p>When controlling cyber–physical systems via consensus algorithms, the robustness issue is of paramount importance because of model mismatching and/or disturbances that generally modify the Laplacian flow dynamics associated to the overall network, compromising the possibility to achieve any expected, orchestrated emergent behavior. To face this issue, the Variable Structure Control (VSC) approach has recently been shown to be an effective tool in designing control protocols over networks, providing robustness and often yielding finite-time convergence. Moreover, VSC further enables the decoupling of simultaneous control objectives where reaching a consensus state is only part of a more complex task, for instance as it happens in distributed optimization. Thus motivated, this paper overviews, from a tutorial perspective, some selected recent advances in the application of VSC with Sliding Modes to design robust consensus controllers in both the leader-less and the leader-following settings. Efforts are also made to unify the notation and to discuss the theoretical foundations of the nonsmooth analysis tools at the basis of their design for a wide readership unfamiliar with these problems and formal tools. To this aim, examples supporting the treatment, and numerical simulations, are given and discussed in detail. Finally, hints for future investigations along with some current open problems are provided.</p></div>","PeriodicalId":50750,"journal":{"name":"Annual Reviews in Control","volume":"55 ","pages":"Pages 338-355"},"PeriodicalIF":9.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49762811","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

Guarantees for data-driven control of nonlinear systems using semidefinite programming: A survey 用半有限编程保证非线性系统的数据驱动控制：调查

IF 9.4 2区计算机科学

Annual Reviews in Control Pub Date : 2023-01-01 DOI: 10.1016/j.arcontrol.2023.100911

Tim Martin , Thomas B. Schön , Frank Allgöwer

{"title":"Guarantees for data-driven control of nonlinear systems using semidefinite programming: A survey","authors":"Tim Martin , Thomas B. Schön , Frank Allgöwer","doi":"10.1016/j.arcontrol.2023.100911","DOIUrl":"10.1016/j.arcontrol.2023.100911","url":null,"abstract":"<div><p><span><span>This survey presents recent research on determining control-theoretic properties and designing controllers with rigorous guarantees using semidefinite programming and for nonlinear systems for which no mathematical models but measured trajectories are available. Data-driven control techniques have been developed to circumvent a time-consuming modelling by first principles and because of the increasing availability of data. Recently, this research field has gained increased attention by the application of Willems’ fundamental lemma, which provides a fertile ground for the development of data-driven control schemes with guarantees for linear time-invariant systems. While the fundamental lemma can be generalized to further system classes, there does not exist a comparable data-based system representation for nonlinear systems. At the same time, nonlinear systems constitute the majority of practical systems. Moreover, they include additional challenges such as data-based </span>surrogate models that prevent system analysis and </span>controller design<span> by convex optimization. Therefore, a variety of data-driven control approaches has been developed with different required prior insights into the system to ensure a guaranteed inference. In this survey, we will discuss developments in the context of data-driven control for nonlinear systems. In particular, we will focus on methods based on system representations providing guarantees from finite data, while the analysis and the controller design boil down to convex optimization problems<span> given as semidefinite programming. Thus, these approaches achieve reasonable advances compared to the state-of-the-art system analysis and controller design by models from system identification. Specifically, the paper covers system representations based on extensions of Willems’ fundamental lemma, set membership, kernel techniques, the Koopman operator, and feedback linearization.</span></span></p></div>","PeriodicalId":50750,"journal":{"name":"Annual Reviews in Control","volume":"56 ","pages":"Article 100911"},"PeriodicalIF":9.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135455293","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

Handbook of linear data-driven predictive control: Theory, implementation and design 线性数据驱动预测控制手册:理论、实现与设计

IF 9.4 2区计算机科学

Annual Reviews in Control Pub Date : 2023-01-01 DOI: 10.1016/j.arcontrol.2023.100914

P.C.N. Verheijen, V. Breschi, M. Lazar

{"title":"Handbook of linear data-driven predictive control: Theory, implementation and design","authors":"P.C.N. Verheijen, V. Breschi, M. Lazar","doi":"10.1016/j.arcontrol.2023.100914","DOIUrl":"10.1016/j.arcontrol.2023.100914","url":null,"abstract":"<div><p>Data-driven predictive control (DPC) has gained an increased interest as an alternative to model predictive control in recent years, since it requires less system knowledge for implementation and reliable data is commonly available in smart engineering systems. Several data-driven predictive control algorithms have been developed recently, which largely follow similar approaches, but with specific formulations and tuning parameters. This review aims to provide a structured and accessible guide on linear data-driven predictive control methods and practices for people in both academia and the industry seeking to approach and explore this field. To do so, we first discuss standard methods, such as subspace predictive control (SPC), and data-enabled predictive control (DeePC), but we also include newer hybrid approaches to DPC, such as <span><math><mi>γ</mi></math></span>–data-driven predictive control and generalized data-driven predictive control. For all presented data-driven predictive controllers we provide a detailed analysis regarding the underlying theory, implementation details and design guidelines, including an overview of methods to guarantee closed-loop stability and promising extensions towards handling nonlinear systems. The performance of the reviewed DPC approaches is compared via simulations on two benchmark examples from the literature, allowing us to provide a comprehensive overview of the different techniques in the presence of noisy data.</p></div>","PeriodicalId":50750,"journal":{"name":"Annual Reviews in Control","volume":"56 ","pages":"Article 100914"},"PeriodicalIF":9.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1367578823000780/pdfft?md5=6b2e8bdfe4a714ce8d0101396d9d6243&pid=1-s2.0-S1367578823000780-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135563271","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}

引用次数: 0

Lyapunov stability tests for linear time-delay systems 线性时滞系统的Lyapunov稳定性检验

IF 9.4 2区计算机科学

Annual Reviews in Control Pub Date : 2022-07-25 DOI: 10.48550/arXiv.2207.12462

Sabine Mondi'e, A. Egorov, M. A. Gómez

引用次数: 10

Linear quantum systems: a tutorial 线性量子系统:教程

IF 9.4 2区计算机科学

Annual Reviews in Control Pub Date : 2022-05-01 DOI: 10.48550/arXiv.2205.04080

Guofeng Zhang, Z. Dong

{"title":"Linear quantum systems: a tutorial","authors":"Guofeng Zhang, Z. Dong","doi":"10.48550/arXiv.2205.04080","DOIUrl":"https://doi.org/10.48550/arXiv.2205.04080","url":null,"abstract":"The purpose of this tutorial is to give a brief introduction to linear quantum control systems. The mathematical model of linear quantum control systems is presented ﬁrst, then some fundamental control-theoretic notions such as stability, controllability and observability are given, which are closely related to several important concepts in quantum information science such as decoherence-free subsystems, quantum nondemolition variables, and back-action evasion measurements. After that, quantum Gaussian states are introduced, in particular, an information-theoretic uncertainty relation is presented which often gives a better bound for mixed Gaussian states than the well-known Heisenberg uncertainty relation. The quantum Kalman ﬁlter is presented for quantum linear systems, which is the quantum analogy of the Kalman ﬁlter for classical (namely, non-quantum-mechanical) linear systems. The quantum Kalman canonical decomposition for quantum linear systems is recorded, and its application is illustrated by means of a recent experiment. As single- and multi-photon states are useful resources in quantum information technology, the response of quantum linear systems to these types of input is presented. Finally, coherent feedback control of quantum linear systems is brieﬂy introduced, and a recent experiment is used to demonstrate the eﬀectiveness of quantum linear systems and networks theory.","PeriodicalId":50750,"journal":{"name":"Annual Reviews in Control","volume":"49 1","pages":"274-294"},"PeriodicalIF":9.4,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86791145","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: 10

Control of cooperative manipulator-endowed systems under high-level tasks and uncertain dynamics 高阶任务和不确定动态下的协作机器人系统控制

IF 9.4 2区计算机科学

Annual Reviews in Control Pub Date : 2022-01-01 DOI: 10.1016/j.arcontrol.2022.09.004

Christos K. Verginis , Dimos V. Dimarogonas

{"title":"Control of cooperative manipulator-endowed systems under high-level tasks and uncertain dynamics","authors":"Christos K. Verginis , Dimos V. Dimarogonas","doi":"10.1016/j.arcontrol.2022.09.004","DOIUrl":"10.1016/j.arcontrol.2022.09.004","url":null,"abstract":"<div><p>This paper considers the problem of distributed motion- and task-planning of multi-agent and multi-agent-object systems under temporal-logic-based tasks and uncertain dynamics. We focus on manipulator-endowed robotic agents that can interact with their surroundings. We present first continuous control algorithms for multi-agent navigation and cooperative object manipulation that exhibit the following properties. First, they are distributed in the sense that each agent calculates its own control signal from local interaction with the other agents and the environment. Second, they guarantee safety properties in terms of inter-agent collision avoidance and obstacle avoidance. Third, they adapt on-the-fly to dynamic uncertainties and are robust to exogenous disturbances. The aforementioned algorithms allow the abstraction of the underlying system to a finite-state representation. Inspired by formal-verification techniques, we use such a representation to derive plans for the agents that satisfy the given temporal-logic tasks. Various simulation results and hardware experiments verify the efficiency of the proposed algorithms.</p></div>","PeriodicalId":50750,"journal":{"name":"Annual Reviews in Control","volume":"54 ","pages":"Pages 219-240"},"PeriodicalIF":9.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1367578822000980/pdfft?md5=49c495bc749b8e5fedb05c72da854f6e&pid=1-s2.0-S1367578822000980-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89804076","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}

引用次数: 2

Special section on estimation and control of quantum systems 量子系统的估计和控制

IF 9.4 2区计算机科学

Annual Reviews in Control Pub Date : 2022-01-01 DOI: 10.1016/j.arcontrol.2022.10.001

Ian R. Petersen, Daoyi Dong

引用次数: 0

Special Section on Analysis and control design for neurodynamics 神经动力学分析与控制设计专区

IF 9.4 2区计算机科学

Annual Reviews in Control Pub Date : 2022-01-01 DOI: 10.1016/j.arcontrol.2022.09.007

Sérgio Pequito, Erfan Nozari, Fabio Pasqualetti

引用次数: 0