Closing loops has been a key paradigm in automatic control for a long time, enabling better and more consistent performance of the underlying processes around which control loops were closed. Control was one of several enablers for the first three industrial revolutions. During most time since the introduction of digital technologies for closed-loop control, memory, processing power and communication bandwidth limitations were the active constraints towards the application of advanced control concepts in industry. During the last two decades, the continued advances in underlying information technologies delivered by "Moore's law" have gradually lifted those constraints, except for the most complex control problems. Today, efforts related to process modelling and control engineering are increasingly the active constraints that limit further progress. Automation continues to evolve, from originally isolated applications to today's typically connected ones, towards more collaborative and, ultimately, more autonomous operations. Latest with the declaration of a "Fourth Industrial Revolution" since 2012, work has been intensified on deploying new sensing and information technologies towards closing new loops. Beyond traditional variables, such as throughput or product quality, availability and performance of the production assets are being added to the consideration., Self-configuration, mass customization and, more generally, the automation of knowledge work are declared as objectives. Information is combined across the traditionally separate operations and enterprise/IT domains and different sensors, models, and algorithms are required to extend close-loop control concepts to a much broader domain. This presentation aims at presenting a snapshot of this development from an industrial perspective, using current industrial application examples to identify both actual progress and areas for further research and development.

The concept of Smart City is gaining popular attention with the goal of sustainability and efficiency, the needs of enhancing quality and performance, and the explosion of technological advances in communication and computation. Given that 50% of the world's population lives in urban regions, critical infrastructures of energy, transportation, and health and their growing interdependencies have to be collectively analyzed and designed to provide the substrate for the realization of the Smart City Concept. This talk will address one of these infrastructures, of Urban Mobility in Transportation. With the growth and expansion of many large metropolitan centers in the last few decades, the problem of traffic congestion continues to grow and vex commuters, commercial drivers, city planners and officials, and environmentalists worldwide. Over 1 billion vehicles travel on the roads today, and that number is projected to double by 2020. Driving a car is an unavoidable choice for at least 50% of city populations, who rely on their vehicles to get to school or to work. When it comes to mobility, tremendous number of opportunities exist for the deployment of dynamic and real-time solutions using availability of data, fast and reliable communication, and ease of computation using the cloud and edge intelligence. This talk will examine one such solution, of Transactive Control, the concept of feedback through economic transactions, for Urban Mobility. Two specific examples of transactive control will be addressed, the first of which is the synthesis of dynamic toll prices with the goal of reducing traffic congestion in highways. The second example of transactive control is in the context of Mobility on Demand, where new modes of transportation other than private and public are being proposed, providing a smorgasbord of options for passengers. In both cases, the use of dynamic tariffs and feedback control principles using computational and dynamic models of the underlying socio-technical system including the transportation network and behavioral models of drivers and riders will be explored.

In the era of Big Data, the continuous explosive growth of digital archives is driving the demand for cost-effective storage technologies. Magnetic tape systems constitute an integral part of current tiered storage infrastructures and are well suited for long- term data storage thanks to their low total cost of ownership, low power consumption, very high reliability and long media lifetime. To meet the growing need for cost-effective storage, it is critical to continue to scale the areal density and the cartridge capacity of tape systems. Key elements towards target tape capacities of 100 TB and beyond are enhanced track-following servo technologies, which allow positioning control on flexible tape media down to the nanometer scale. Furthermore, accurate tape tension and velocity control during tape transport will enable the use of thinner tape, which in turn enables increased cartridge capacity. In this talk, the focus is on advanced technologies for tape transport and track-following control that achieve nanoscale positioning as well as their role in today’s and future tape storage systems.