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A frequency-domain approach for enhanced performance and task flexibility in finite-time ILC 在有限时间 ILC 中提高性能和任务灵活性的频域方法
IF 2.5 3区 计算机科学
European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101033
Max van Haren , Kentaro Tsurumoto , Masahiro Mae , Lennart Blanken , Wataru Ohnishi , Tom Oomen
{"title":"A frequency-domain approach for enhanced performance and task flexibility in finite-time ILC","authors":"Max van Haren ,&nbsp;Kentaro Tsurumoto ,&nbsp;Masahiro Mae ,&nbsp;Lennart Blanken ,&nbsp;Wataru Ohnishi ,&nbsp;Tom Oomen","doi":"10.1016/j.ejcon.2024.101033","DOIUrl":"10.1016/j.ejcon.2024.101033","url":null,"abstract":"<div><div>Iterative learning control (ILC) techniques are capable of improving the tracking performance of control systems that repeatedly perform similar tasks by utilizing data from past iterations. The aim of this paper is to achieve both the task flexibility enabled by ILC with basis functions and the performance of frequency-domain ILC, with an intuitive design procedure. The cost function of norm-optimal ILC is determined that recovers frequency-domain ILC, and consequently, the feedforward signal is parameterized in terms of basis functions and frequency-domain ILC. The resulting method has the performance and design procedure of frequency-domain ILC and the task flexibility of basis functions ILC, and are complimentary to each other. Validation on a benchmark example confirms the capabilities of the framework.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"80 ","pages":"Article 101033"},"PeriodicalIF":2.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141510831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Decentralized PI-control and anti-windup in resource sharing networks 资源共享网络中的分散 PI 控制和防倒转功能
IF 2.5 3区 计算机科学
European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101049
Felix Agner , Jonas Hansson , Pauline Kergus , Anders Rantzer , Sophie Tarbouriech , Luca Zaccarian
{"title":"Decentralized PI-control and anti-windup in resource sharing networks","authors":"Felix Agner ,&nbsp;Jonas Hansson ,&nbsp;Pauline Kergus ,&nbsp;Anders Rantzer ,&nbsp;Sophie Tarbouriech ,&nbsp;Luca Zaccarian","doi":"10.1016/j.ejcon.2024.101049","DOIUrl":"10.1016/j.ejcon.2024.101049","url":null,"abstract":"<div><div>We consider control of multiple stable first-order agents which have a control coupling described by an M-matrix. These agents are subject to incremental sector-bounded input nonlinearities. We show that such plants can be globally asymptotically stabilized to a unique equilibrium using fully decentralized proportional–integral controllers equipped with anti-windup and subject to local tuning rules. In addition, we show that when the nonlinearities correspond to the saturation function, the closed loop asymptotically minimizes a weighted 1-norm of the agents state mismatch. The control strategy is finally compared to other state-of-the-art controllers on a numerical district heating example.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"80 ","pages":"Article 101049"},"PeriodicalIF":2.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141406400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Scaled graphs for reset control system analysis 用于复位控制系统分析的比例图
IF 2.5 3区 计算机科学
European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101050
Sebastiaan van den Eijnden , Thomas Chaffey , Tom Oomen , W.P.M.H. (Maurice) Heemels
{"title":"Scaled graphs for reset control system analysis","authors":"Sebastiaan van den Eijnden ,&nbsp;Thomas Chaffey ,&nbsp;Tom Oomen ,&nbsp;W.P.M.H. (Maurice) Heemels","doi":"10.1016/j.ejcon.2024.101050","DOIUrl":"10.1016/j.ejcon.2024.101050","url":null,"abstract":"<div><div>Scaled graphs allow for graphical analysis of nonlinear systems, but are generally difficult to compute. The aim of this paper is to develop a method for approximating the scaled graph of reset controllers. A key ingredient in our approach is the generalized Kalman–Yakubovich–Popov lemma to determine <em>input specific</em> input–output properties of a reset controller in the time domain. By combining the obtained time domain properties to cover the full input space, an over-approximation of the scaled graph is constructed. Using this approximation, we establish a feedback interconnection result and provide connections to classical input–output analysis frameworks. Several examples show the relevance of the results for the analysis and design of reset control systems.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"80 ","pages":"Article 101050"},"PeriodicalIF":2.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141398765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Peak estimation of rational systems using convex optimization 利用凸优化进行有理系统的峰值估计
IF 2.5 3区 计算机科学
European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101088
Jared Miller, Roy S. Smith
{"title":"Peak estimation of rational systems using convex optimization","authors":"Jared Miller,&nbsp;Roy S. Smith","doi":"10.1016/j.ejcon.2024.101088","DOIUrl":"10.1016/j.ejcon.2024.101088","url":null,"abstract":"<div><div>This paper presents algorithms that upper-bound the peak value of a state function along trajectories of a continuous-time system with rational dynamics. The finite-dimensional but nonconvex peak estimation problem is cast as a convex infinite-dimensional linear program in occupation measures. This infinite-dimensional program is then truncated into finite-dimensions using the moment-Sum-of-Squares (SOS) hierarchy of semidefinite programs. Prior work on treating rational dynamics using the moment-SOS approach involves clearing dynamics to common denominators or adding lifting variables to handle reciprocal terms under new equality constraints. Our solution method uses a sum-of-rational method based on absolute continuity of measures. The Moment-SOS truncations of our program possess lower computational complexity and (empirically demonstrated) higher accuracy of upper bounds on example systems as compared to prior approaches.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"80 ","pages":"Article 101088"},"PeriodicalIF":2.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
A novel MATLAB toolbox for Control101 courses 用于 Control101 课程的新型 MATLAB 工具箱
IF 2.5 3区 计算机科学
European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101041
J.A. Rossiter
{"title":"A novel MATLAB toolbox for Control101 courses","authors":"J.A. Rossiter","doi":"10.1016/j.ejcon.2024.101041","DOIUrl":"10.1016/j.ejcon.2024.101041","url":null,"abstract":"<div><div>In recent years the educationally focused parts of the global control community have given some focus to what constitutes a sensible first course in control (Rossiter et al., 2020) and how to support this with high quality learning and teaching resources. This paper contributes to that overall effort in that it provides an example of high quality, open-access resources to support students in their independent learning. One aspect of the <em>ideal</em> first course in control is the suggestion that we (the community) focus more on concepts and understanding and less on tedious paper and pen calculations; to do this the community needs suitable easy to use software for performing computations and producing illustrations. Hence the author is leading what he hopes will be a collaborative community project on creating a MATLAB toolbox to provide such software. The purpose of this paper is to highlight the toolbox, present its current contents and thus enable staff to evaluate and adopt this toolbox and moreover, to reflect on how it might be improved.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"80 ","pages":"Article 101041"},"PeriodicalIF":2.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141407183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
On modeling collective risk perception via opinion dynamics 通过舆论动力学建立集体风险认知模型
IF 2.5 3区 计算机科学
European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101036
Lorenzo Zino , Francesca Giardini , Daniele Vilone , Ming Cao
{"title":"On modeling collective risk perception via opinion dynamics","authors":"Lorenzo Zino ,&nbsp;Francesca Giardini ,&nbsp;Daniele Vilone ,&nbsp;Ming Cao","doi":"10.1016/j.ejcon.2024.101036","DOIUrl":"10.1016/j.ejcon.2024.101036","url":null,"abstract":"<div><div>Modeling the collective response to an emergency is a problem of paramount importance in social science and risk management. Here, we leverage the social psychology literature to develop a mathematical model tailored to such a real-world problem, grounded in the opinion dynamics theory. In our model, a network of individuals revise their risk perception by processing information broadcast by the institution and shared by peers, and accounts for heterogeneity in terms of individuals’ trust in institutions, peers, and in their own risk sensitivity. Through a rigorous analysis of the model, we establish that the temporal average opinions of the individuals converge to a steady state and, under some assumptions, we are able to analytically characterize such a steady state, shedding light on how the individuals’ heterogeneous risk sensitivity shapes the collective response. Numerical results and simulations are provided to illustrate and corroborate our findings.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"80 ","pages":"Article 101036"},"PeriodicalIF":2.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141408434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Distributed online constrained convex optimization with event-triggered communication 带事件触发通信的分布式在线约束凸优化
IF 2.5 3区 计算机科学
European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101042
Kunpeng Zhang , Xinlei Yi , Yuzhe Li , Ming Cao , Tianyou Chai , Tao Yang
{"title":"Distributed online constrained convex optimization with event-triggered communication","authors":"Kunpeng Zhang ,&nbsp;Xinlei Yi ,&nbsp;Yuzhe Li ,&nbsp;Ming Cao ,&nbsp;Tianyou Chai ,&nbsp;Tao Yang","doi":"10.1016/j.ejcon.2024.101042","DOIUrl":"10.1016/j.ejcon.2024.101042","url":null,"abstract":"<div><div>This paper focuses on the distributed online convex optimization problem with time-varying inequality constraints over a network of agents, where each agent collaborates with its neighboring agents to minimize the cumulative network-wide loss over time. To reduce communication overhead between the agents, we propose a distributed event-triggered online primal–dual algorithm over a time-varying directed graph. With several classes of appropriately chose decreasing parameter sequences and non-increasing event-triggered threshold sequences, we establish dynamic network regret and network cumulative constraint violation bounds. Finally, a numerical simulation example is provided to verify the theoretical results.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"80 ","pages":"Article 101042"},"PeriodicalIF":2.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141510837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Stochastic control with distributionally robust constraints for cyber–physical systems vulnerable to attacks 为易受攻击的网络物理系统提供具有分布稳健约束的随机控制
IF 2.5 3区 计算机科学
European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101044
Nishanth Venkatesh , Aditya Dave , Ioannis Faros , Andreas A. Malikopoulos
{"title":"Stochastic control with distributionally robust constraints for cyber–physical systems vulnerable to attacks","authors":"Nishanth Venkatesh ,&nbsp;Aditya Dave ,&nbsp;Ioannis Faros ,&nbsp;Andreas A. Malikopoulos","doi":"10.1016/j.ejcon.2024.101044","DOIUrl":"10.1016/j.ejcon.2024.101044","url":null,"abstract":"<div><div>In this paper, we investigate the control of a cyber–physical system (CPS) while accounting for its vulnerability to external attacks. We formulate a constrained stochastic problem with a robust constraint to ensure robust operation against potential attacks. We seek to minimize the expected cost subject to a constraint limiting the worst-case expected damage an attacker can impose on the CPS. We present a dynamic programming decomposition to compute the optimal control strategy in this robust-constrained formulation and prove its recursive feasibility. We also illustrate the utility of our results by applying them to a numerical simulation.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"80 ","pages":"Article 101044"},"PeriodicalIF":2.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141530176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Regret optimal control for uncertain stochastic systems 不确定随机系统的遗憾优化控制
IF 2.5 3区 计算机科学
European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101051
Andrea Martin , Luca Furieri , Florian Dörfler , John Lygeros , Giancarlo Ferrari-Trecate
{"title":"Regret optimal control for uncertain stochastic systems","authors":"Andrea Martin ,&nbsp;Luca Furieri ,&nbsp;Florian Dörfler ,&nbsp;John Lygeros ,&nbsp;Giancarlo Ferrari-Trecate","doi":"10.1016/j.ejcon.2024.101051","DOIUrl":"10.1016/j.ejcon.2024.101051","url":null,"abstract":"<div><div>We consider control of uncertain linear time-varying stochastic systems from the perspective of regret minimization. Specifically, we focus on the problem of designing a feedback controller that minimizes the loss relative to a clairvoyant optimal policy that has foreknowledge of both the system dynamics and the exogenous disturbances. In this competitive framework, establishing robustness guarantees proves challenging as, differently from the case where the model is known, the clairvoyant optimal policy is not only inapplicable, but also impossible to compute without knowledge of the system parameters. To address this challenge, we embrace a scenario optimization approach, and we propose minimizing regret robustly over a finite set of randomly sampled system parameters. We prove that this policy optimization problem can be solved through semidefinite programming, and that the corresponding solution retains strong probabilistic out-of-sample regret guarantees in face of the uncertain dynamics. Our method naturally extends to include satisfaction of safety constraints with high probability. We validate our theoretical results and showcase the potential of our approach by means of numerical simulations.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"80 ","pages":"Article 101051"},"PeriodicalIF":2.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141578081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Data-driven uncertainty propagation for stochastic predictive control of multi-energy systems 多能源系统随机预测控制的数据驱动不确定性传播
IF 2.5 3区 计算机科学
European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101066
M. Batu Özmeteler , Deborah Bilgic , Guanru Pan , Alexander Koch , Timm Faulwasser
{"title":"Data-driven uncertainty propagation for stochastic predictive control of multi-energy systems","authors":"M. Batu Özmeteler ,&nbsp;Deborah Bilgic ,&nbsp;Guanru Pan ,&nbsp;Alexander Koch ,&nbsp;Timm Faulwasser","doi":"10.1016/j.ejcon.2024.101066","DOIUrl":"10.1016/j.ejcon.2024.101066","url":null,"abstract":"<div><div>Stochastic predictive control schemes that account for epistemic and aleatoric uncertainties, i.e. lack of model knowledge and stochastic disturbances, are of major interest for multi-energy systems. However, there exists a trade-off between model complexity, computational effort, and accuracy of uncertainty quantification. This paper attempts to assess this trade-off by comparing a recently proposed approach combining Willems’ fundamental lemma with polynomial chaos expansion to a model-based scheme that first propagates uncertainty with PCE and then considers chance constraints in the optimization. The simulation results show that the data-driven scheme yields similar performance and computational efficiency compared to the model-based scheme, with the advantage of avoiding the construction of explicit models.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"80 ","pages":"Article 101066"},"PeriodicalIF":2.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141722045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
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