Authors:
Jonathan P. How;
Pages: 3 - 5 Abstract: Presents the introductory editorial for this issue of the publication. PubDate:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Authors:
Jonathan P. How;
Pages: 6 - 9 Abstract: Brief discusses the articles that are presented in this issue of the publication which focus on off-road vehicle control. PubDate:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Authors:
Bob Bitmead;
Pages: 10 - 11 Abstract: Presents the President’s message for this issue of the publication. PubDate:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Pages: 13 - 14 Abstract: Skilled behavior involves the effective use of knowledge in execution or performance. A skill may require dexterity or coordination and generally develops over time through learning. This work focuses on employing learning to enable a robot to acquire skills, particularly physical skills where learning control is required. The requirements are i) dealing with nonlinearity/complex dynamics, ii) achieving robust performance under uncertainty, and iii) learning control actions when feedback is delayed and minimal. PubDate:
Feb. 2019
Issue No:Vol. 39, No. 1 (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:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Authors:
Bayu Jayawardhana;Steffen Waldherr;
Pages: 15 - 24 Abstract: Presents information of the CS society Technical Committee on Systems Biology. PubDate:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Pages: 16 - 18 Abstract: How did your education and early career lead to your initial and continuing interest in the control field' PubDate:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Pages: 18 - 21 Abstract: How did your education and early career lead to your initial and continuing interest in the control field' PubDate:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Pages: 21 - 22 Abstract: How did your education and early career lead to your initial and continuing interest in the control field' PubDate:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Pages: 23 - 24 Abstract: How did your education and early career lead to your initial and continuing interest in the control field' PubDate:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Authors:
Brian Goldfain;Paul Drews;Changxi You;Matthew Barulic;Orlin Velev;Panagiotis Tsiotras;James M. Rehg;
Pages: 26 - 55 Abstract: The technical challenge of creating a self-driving vehicle remains an open problem despite significant advancements from universities, car manufacturers, and technology companies. Full autonomy, known as level 5 (see "Society of Automotive Engineers Levels of Driving Automation"), is defined as full-time performance by an automated driving system of all aspects of the dynamic driving task under all roadway and environmental conditions that can be managed by a human driver. It is estimated that level 5 autonomous vehicles on public roads will help eliminate more than 90% [1] of the 35,000 annual traffic fatalities caused by human error in the United States [2]; reduce commute time, road congestion, and pollution; and increase driving resource utilization [3]. PubDate:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Authors:
Stacy D. Hill;James C. Spall;
Pages: 56 - 67 Abstract: Markov chain Monte Carlo (MCMC) is a versatile sampling approach that is useful in a wide range of estimation and simulation applications. Fundamentally, MCMC is a powerful general means of generating random samples from probability distributions from which it is otherwise difficult to draw samples. The MCMC method is named for its reliance on the construction of a Markovian (dependent) sequence of random variables. Under modest conditions, the sequence has a limiting probability distribution that corresponds to the distribution of interest, often called the target distribution. The sequence, as will be seen, is easily constructed, and the target distribution may be almost any distribution of interest. These two features of MCMC make it a popular choice for Monte Carlo simulation. The primary forms of MCMC are the Metropolis-Hastings (M-H) algorithm and Gibbs sampling. Although both forms are useful, we focus on M-H, which is more flexible and easier to implement. A general discussion of many aspects of MCMC, including several examples, is given in [1]. As discussed in "Summary," the purpose of this article is to provide some of the theoretical support for M-H that was not given in [1], focusing specifically on the stationarity and convergence of the underlying Markov process. PubDate:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Authors:
Christos G. Cassandras;
Pages: 68 - 71 Abstract: This book focuses on the control of transportation systems, theories of traffic control, and highway management. This book is a welcome contribution that focuses on the all-important freeway component of transportation systems. Its aim is to provide an overview of modeling approaches and traffic control methods in a comprehensive manner without sacrificing rigor. It is an ideal text for a motivated control engineer who decides to enter this field. For a curious control theorist who wishes to learn more about traffic systems at an introductory level, there is something for everyone to find a connection to: models using partial differential equations or discrete event systems, estimation methods that include consensus-based ideas, control using classical proportional-integral methods or more modern model predictive control techniques, and optimization aimed at improving overall system performance. Finally, the authors added an innovative component that considers sustainable and environment-friendly freeway traffic systems. PubDate:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Pages: 71 - 86 Abstract: Presents a summary of recent books of interest to control systems engineers. PubDate:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Authors:
Martin Steinberger;Martin Horn;Leonid Fridman;
Pages: 79 - 80 Abstract: Presents information on the 15th International Workshop on Variable Structure Systems and Sliding Mode Control. PubDate:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Authors:
Abhishek Halder;Ricardo G. Sanfelice;
Pages: 80 - 81 Abstract: Presents information on the CPAR Control Theory and Automation Symposium. PubDate:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Authors:
Douglas A. Lawrence;
Pages: 82 - 86 Abstract: Presents informationon the 2019 American Control Conference. PubDate:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Pages: 88 - 88 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:
Feb. 2019
Issue No:Vol. 39, No. 1 (2019)
Hybrid journal (It can contain Open Access articles)
