Is the current control theory enough?

Abstract

The 4th industrial revolution imposes new challenges to education in control engineering and automation. Control engineering and automation have been consolidated as an actual science of decision making, since contrary to traditional decision-making paradigms, control engineering has contemplated the dynamic and feedback effects from its inception. Nowadays the applications have overcome the traditional areas of process control, power systems or aeronautical systems, to enter in areas such as bioengineering, medicine, finance, mobility management, logistics and transport, appliances, entertainment, urban infrastructures, to mention just a few.
Technological developments confront us with a new paradigm, in which the proliferation of sensors marks a steady trend that leads us to the paradox of having lots of data, but not necessarily more information. The sensors communicate with control centers through telematic networks that have delays or packet losses. The sensors, although every day cheaper, are not necessarily accurate. Therefore, the is a need for integration of data validation systems into the control architectures with information processing capabilities of heterogeneous and massive data sources (video, sound, LIDAR, radar, etc.)
Communication and information give way to one of the most critical forces in the human species and nature: cooperation. Cooperation demands an effort of coordination, negotiation and decision making, increasing the benefit that each agent or entity, separately, must perceive or achieve. The development of coordinated tasks requires a knowledge of the capabilities of each entity and the mechanisms of interaction so that the level of detail of that knowledge increases the effectiveness of the interaction.
The interaction between machines (M2M) is a distinctive feature of the 4th industrial revolution is. A performant control task demands the exchange, not only of data, measurements, and actions but also the exchange of interaction models. Reaching that level of sophistication demands interaction architectures that allow replacing units without the need to modify the coordination architecture, cooperation or control algorithms.
This panorama confronts us with the questions: "Is the current control theory enough?" and what new elements should be considered in the training, education and exercise of control engineering and automation?