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Authors:
Rodolphe Sepulchre;
Pages: 3 - 4 Abstract: This is August, and I am returning from a few days far away from work. During those few days, I did my best to stay away from e-mails, to read on paper rather than on screen, to write with pen rather than with a keyboard, to stay outside rather than inside. Holy days. Days of respiration. Days of encounters. PubDate:
TUE, 14 NOV 2023 09:16:39 -04 Issue No:Vol. 43, No. 6 (2023)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
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Authors:
Rodolphe Sepulchre;
Pages: 5 - 7 Abstract: This issue of IEEE Control Systems is the second of two special issues devoted to data-driven control. The guest editor for these issues is Florian Dörfler, and he was helped by our Associate Editor Daniel Quevedo. PubDate:
TUE, 14 NOV 2023 09:16:38 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Magnus Egerstedt;
Pages: 8 - 10 Abstract: The way we have structured our conferences for as long as I have been an active participant in the IEEE Control Systems Society (CSS) is some variation of the formula of each talk being 20 min long; each session consisting of six presentations, with around 25 (this fluctuates a bit) parallel sessions; and three such blocks per day, with the conferences lasting three days. This translates to 1,350 presentations (not counting plenaries, workshops, and some special presentations) or a total of 18 days and 18 h of effective speaking time. Apart from the mysticism surrounding the number 18, one can (and probably should) ask if this is really the best use of the meeting space, the nontrivial carbon footprint the participants incur when traveling to the meetings, the evolving technological tools out there to help facilitate presentations, and our time. PubDate:
TUE, 14 NOV 2023 09:16:39 -04 Issue No:Vol. 43, No. 6 (2023)
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Pages: 11 - 13 Abstract: In this issue, “25 Years Ago” revisits the article “Sensor-Based Microassembly of Hybrid MEMS Devices” by Bradley Nelson, Yu Zhou, and Barmeshwar Vikramaditya in IEEE Control Systems Magazine, vol. 18, no. 6, pp. 35–45. Below is an excerpt from the article. PubDate:
TUE, 14 NOV 2023 09:16:38 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Masayuki Fujita;Alf Isaksson;
Pages: 14 - 14 Abstract: Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers. PubDate:
TUE, 14 NOV 2023 09:16:39 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Yoshio Ebihara;
Pages: 15 - 16 Abstract: Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers. PubDate:
TUE, 14 NOV 2023 09:16:38 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Rodolphe Sepulchre;
Pages: 17 - 17 Abstract: In this issue of IEEE Control Systems, we speak with Marc Bodson, who is a professor of electrical and computer engineering at the University of Utah, Salt Lake City, UT, USA; Shun-ichi Azuma, who is a professor at Kyoto University, Kyoto, Japan; and Serdar Yüksel, who is a professor in the Department of Mathematics and Statistics, Queen’s University, Kingston, ON, Canada. PubDate:
TUE, 14 NOV 2023 09:16:39 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Marc Bodson;
Pages: 18 - 21 Abstract: Q. How did your education and early career lead to your initial and continuing interest in the control field' PubDate:
TUE, 14 NOV 2023 09:16:39 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Shun-Ichi Azuma;
Pages: 21 - 23 Abstract: Q. How did your education and early career lead to your initial and continuing interest in the control field' PubDate:
TUE, 14 NOV 2023 09:16:39 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Serdar Yüksel;
Pages: 24 - 26 Abstract: Q. How did your education and early career lead to your initial and continuing interest in the control field' PubDate:
TUE, 14 NOV 2023 09:16:38 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Florian Dörfler;
Pages: 27 - 31 Abstract: A recurring question that all authors of this special issue encounter is, “Why not go with models'” Two terms need to be clarified: In this context, a model is understood as a parametric system representation often endowed with an interpretable structure, for example, a state-space representation with a readily discernible F = m · a equation. Further, the term data-driven control, as we employ it in this special issue, is not just about using data from a black box to inform decision making. Researchers are exploring different paradigms, among others, model-based control design, where the model and uncertainty estimates are learned from data using contemporary system identification and uncertainty quantification techniques. In classical adaptive control terminology [1], [2], this two-stage approach is referred to as indirect. In contrast, direct data-driven control bypasses models in the decision making; see Figure 1 for a graphical illustration of the two paradigms. Hence, the more precise question should be, “When should we embrace direct or indirect data-driven control'” I will delve into the expected “it depends” answer in this “Editorial” column. PubDate:
TUE, 14 NOV 2023 09:16:38 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Henk J. Van Waarde;Jaap Eising;M. Kanat Camlibel;Harry L. Trentelman;
Pages: 32 - 66 Abstract: Roughly speaking, systems and control theory deals with the problem of making a concrete physical system behave according to certain desired specifications. To achieve this desired behavior, the system can be interconnected with a physical device, called a controller. The problem of finding a mathematical description of such a controller is called the control design problem. PubDate:
TUE, 14 NOV 2023 09:16:38 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Anastasios Tsiamis;Ingvar Ziemann;Nikolai Matni;George J. Pappas;
Pages: 67 - 97 Abstract: Learning algorithms have become an integral component to modern engineering solutions. Examples range from self-driving cars and recommender systems to finance and even critical infrastructure, many of which are typically under the purview of control theory. While these algorithms have already shown tremendous promise in certain applications [1], there are considerable challenges, in particular, with respect to guaranteeing safety and gauging fundamental limits of operation. Thus, as we integrate tools from machine learning into our systems, we also require an integrated theoretical understanding of how they operate in the presence of dynamic and system-theoretic phenomena. Over the past few years, intense efforts toward this goal—an integrated theoretical understanding of learning, dynamics, and control—have been made. While much work remains to be done, a relatively clear and complete picture has begun to emerge for (fully observed) linear dynamical systems. These systems already allow for reasoning about concrete failure modes, thus helping to indicate a path forward. Moreover, while simple at a glance, these systems can be challenging to analyze. Recently, a host of methods from learning theory and high-dimensional statistics, not typically in the control-theoretic toolbox, have been introduced to our community. This tutorial survey serves as an introduction to these results for learning in the context of unknown linear dynamical systems (see “Summary”). We review the current state of the art and emphasize which tools are needed to arrive at these results. Our focus is on characterizing the sample efficiency and fundamental limits of learning algorithms. Along the way, we also delineate a number of open problems. More concretely, this article is structured as follows. We begin by revisiting recent advances in the finite-sample analysis of system identification. Next, we discuss how these finite-sample bounds can be used downstream to give guaranteed performance for learning-based offline control. The final technical section discusses the more challenging online control setting. Finally, in light of the material discussed, we outline a number of future directions. PubDate:
TUE, 14 NOV 2023 09:16:38 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Valentina Breschi;Simone Formentin;
Pages: 98 - 124 Abstract: In many control applications, model-based design has become the standard practice due to the obvious advantages of a convenient, understandable description of the process and the possibility of a continuous validation of the controlled system at all stages of development [1]. PubDate:
TUE, 14 NOV 2023 09:16:38 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Mohammad Khosravi;Rodolphe Sepulchre;
Pages: 125 - 127 Abstract: Q. How would you pitch your Ph.D. research briefly' How would you describe the significance and relevance of your results' PubDate:
TUE, 14 NOV 2023 09:16:39 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Shahriar Talebi;Rodolphe Sepulchre;
Pages: 128 - 167 Abstract: Q. How would you pitch your Ph.D. dissertation in one paragraph' PubDate:
TUE, 14 NOV 2023 09:16:39 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Iman Shames;Robert Mahony;Rodolphe Sepulchre;
Pages: 131 - 133 Abstract: In this issue, we speak with Iman Shames and Robert Mahony about the Control, Information, Intelligence, Communication, Automation, Decision, and Autonomy (CIICADA) Laboratory of the Australian National University. This research laboratory continues the legacy of international research excellence established by Profs. Brian Anderson and John Moore, and provides expertise targeted at Australia’s technological and societal priorities. PubDate:
TUE, 14 NOV 2023 09:16:39 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Liuping Wang;Robin Ping Guan;Kevin L. Moore;
Pages: 134 - 136 Abstract: The book situates itself in a unique niche “between proportional-integral-derivative (PID) and model predictive control (MPC),” as a compromise between the tradeoffs and advantages of each. The book emphasizes state-space techniques but goes beyond the standard presentation of these ideas to consider their application in more traditional industrial settings, where consideration must be given to MIMO dynamics, regulation and setpoint tracking, disturbance rejection, integrator windup, and more. The book shows how to adapt the modern state-space approach to deal with these more classical concepts. At the same time, these adaptations are combined with the state-space design concepts of linear quadratic regulation (LQR) and state estimation through observers and Kalman filters. Readers of the book are thus left with a toolbox that, while not going all of the way to a full MPC framework, marries the practical design consideration of classical control to the power of state-space methods for optimal design of MIMO systems. The book also has an associated companion website for instructors where the MATLAB files and nominal lecture slides can be found. The book's conversational style and ample use of examples make the material easy to understand. Further, it uses a novel approach to introduce integrator-based compensation with antiwindup considerations into state feedback controller design. The book is also valuable in its careful discussion of discrete time implementation of controllers, including the generalization of integrator-based compensation to full internal model control. Finally, the book provides a great introduction to the theory and use of Kalman filters. I would certainly recommend this book as a basis for a second course in control focused on teaching the design of state-space controllers. PubDate:
TUE, 14 NOV 2023 09:16:39 -04 Issue No:Vol. 43, No. 6 (2023)
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Pages: 137 - 137 Abstract: This year, the Technical Committee (TC) Outstanding Student Paper Prizes continued, with seven TCs awarding prizes. These prizes aim to recognize young talent associated with a technical area and promote student membership and participation in the TCs. The prizes are awarded by each TC to a student who is the primary author of a paper at the previous year’s IEEE Conference on Decision and Control (CDC) or the previous year’s IEEE Conference on Control Technology and Applications. The nomination and selection of the prizes are carried out by the TCs, with oversight from the IEEE Control Systems Society vice president for technical activities. PubDate:
TUE, 14 NOV 2023 09:16:38 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Xiaobo Tan;
Pages: 138 - 145 Abstract: Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers. PubDate:
TUE, 14 NOV 2023 09:16:38 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Maria Prandini;Luca Zaccarian;Sophie Tarbouriech;Philipp Braun;
Pages: 146 - 148 Abstract: Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers. PubDate:
TUE, 14 NOV 2023 09:16:39 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Kimon P. Valavanis;
Pages: 149 - 151 Abstract: Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers. PubDate:
TUE, 14 NOV 2023 09:16:38 -04 Issue No:Vol. 43, No. 6 (2023)
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Authors:
Kai Cai;
Pages: 152 - 154 Abstract: Walter Murray Wonham died on Sunday, 14 May 2023 at the age of 88, leaving a series of legacies in control theory (see “Control Theory Legacies”). He died unexpectedly at home in Toronto, Ontario, Canada, and was active in research, graduate teaching and supervision until the day of his death. PubDate:
TUE, 14 NOV 2023 09:16:38 -04 Issue No:Vol. 43, No. 6 (2023)
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Pages: 155 - 161 Abstract: Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers. PubDate:
TUE, 14 NOV 2023 09:16:38 -04 Issue No:Vol. 43, No. 6 (2023)
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Pages: 161 - 167 Abstract: Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers. PubDate:
TUE, 14 NOV 2023 09:16:39 -04 Issue No:Vol. 43, No. 6 (2023)
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Hybrid journal (It can contain Open Access articles)
