Authors:
Jonathan P. How;
Pages: 4 - 6 Abstract: Presents the introductory editorial for this issue of the publication. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Pages: 6 - 6 Abstract: Presents Dr. Arnold Beckman's seven rules for success. Dr. Arnold O. Beckman, scientist, inventor, founder of Beckman Instruments, and philanthropist; posted on the wall at the Arnold and Mabel Beckman Center of the National Academies of Sciences and Engineering, Irvine, California. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Authors:
Jonathan P. How;
Pages: 7 - 10 Abstract: Presents the introductory editorial for this issue of the publication. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Authors:
Bob Bitmead;
Pages: 11 - 12 Abstract: Presents the President's message for this issue of the publication. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Pages: 13 - 14 Abstract: We present the design of a thrust vector controller for a space shuttle vehicle with multiple engines. This controller will maintain vehicle trajectory and thrust vector while minimizing risk and damage to each engine and to the propulsion system as a whole by independently controlling the thrust magnitude and exhaust cone gimbal angles of each engine. A statistical model from reliability theory is used to estimate overall engine damage accumulation and failure risk. An intelligent control system framework, which functionally decomposes the control task into a formal hierarchical structure composed of nominally independent task coordinators, is used to design and analyze the control structure for the entire propulsion system. One subtask that appears repeatedly within the hierarchy is that of distributing the required control actions among multiple engines or actuators dynamically in response to changing damage, risk, and status information. We identify this as the "control relegation problem" and solve it using linear quadratic optimal control techniques with variable weighting matrices. The individual controllers, when integrated into the formal structure, achieve the control objectives while minimizing mission risk and component stress and maximizing operating efficiency. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Pages: 13 - 13 Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Authors:
Bozenna Pasik-Duncan;Linda Bushnell;
Pages: 15 - 16 Abstract: Presents information n the CS society IEEE Women in Engineering's Achieving a Global Impact meeting. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Pages: 20 - 20 Abstract: Reports on the new Deputy Editor-in-Chief for this issue of the publication. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Authors:
Guillaume Mercere;
Pages: 21 - 23 Abstract: Presents information on the CS society Technical Committee on System Identification and Adaptive Control. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Authors:
Jason Siegel;
Pages: 23 - 24 Abstract: Presents information on the CS society Technical Committee on Automotove Control. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Authors:
Solmaz S. Kia;Bryan Van Scoy;Jorge Cortes;Randy A. Freeman;Kevin M. Lynch;Sonia Martinez;
Pages: 40 - 72 Abstract: Technological advances in ad hoc networking and the availability of low-cost reliable computing, data storage, and sensing devices have made scenarios possible where the coordination of many subsystems extends the range of human capabilities. Smart grid operations, smart transportation, smart health care, and sensing networks for environmental monitoring and exploration in hazardous situations are just a few examples of such network operations. In these applications, the ability of a network system to (in a decentralized fashion) fuse information, compute common estimates of unknown quantities, and agree on a common view of the world is critical. These problems can be formulated as agreement problems on linear combinations of dynamically changing reference signals or local parameters. This dynamic agreement problem corresponds to dynamic average consensus, which, as discussed in "Summary," is the problem of interest of this article. The dynamic average consensus problem is for a group of agents to cooperate to track the average of locally available time-varying reference signals, where each agent is capable only of local computations and communicating with local neighbors. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Authors:
Anna Prach;Omran Kouba;Dennis S. Bernstein;
Pages: 73 - 82 Abstract: One of the many things that humans and many animals are very good at is picking up objects. Teaching robots to pick up objects is not so easy, however, for at least two reasons. First, the coefficient of friction may be unknown, and therefore, an object may slip through the robot's grasp. Although this uncertainty can be overcome by using a tighter grip, another issue arises, namely, that excessive force may crush the object. Furthermore, the length of the object must also be accounted for since the ultimate goal is to achieve a slip distance that is less than the length of the object. Consequently, reliable gripping is a control problem that requires a careful tradeoff between the possibility of dropping an object and the potential for crushing it. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Authors:
Syed Aseem Ul Islam;Dennis S. Bernstein;
Pages: 82 - 85 Abstract: Recursive least squares (RLS) is a technique used for minimizing a quadratic cost function, where the minimizer is updated at each step as new data become available. RLS is more computationally efficient than batch least squares, and it is extensively used for system identification and adaptive control. This article derives RLS and emphasizes its real-time implementation in terms of the availability of the data as well as the time needed for the computation. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Authors:
Luca Carlone;
Pages: 86 - 88 Abstract: Presents a listing and summary of new books released on the topic of control systems. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Pages: 89 - 91 Abstract: Presents a listing and summary of new books released on the topic of control systems. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Pages: 91 - 91 Abstract: There are three great pillars of the theory of inequalities: positivity, monotonicity, and convexity. The notions of positivity and monotonicity are so intrinsic to the subject that they serve us steadily without ever calling attention to themselves, but convexity is different. Convexity expresses a second order effect, and for it to provide assistance we almost always need to make some deliberate preparations. —J. Michael Steele, The Cauchy-Schwarz Master Class — An Introduction to the Art of Mathematical Inequalities, p. 87, Cambridge University Press, 2008. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Authors:
Andrew Teel;Magnus Egerstedt;
Pages: 94 - 99 Abstract: Presents information on the 57th IEEE Conference on Decision and Control. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Pages: 101 - 110 Abstract: Presents the minutes of the IEEE Control Systems Society Board of Governors meeting. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Pages: 111 - 111 Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Pages: 112 - 112 Abstract: Various puzzles, quizzes, games, humorous definitions, or mathematical that should engage the interest of readers. PubDate:
June 2019
Issue No:Vol. 39, No. 3 (2019)
Hybrid journal (It can contain Open Access articles)
