Collaborative Research: The value of Information in Networked Control: a Utility Based Approach

This project addresses the problem of determining the quality or value of the information delivered at a given point in space and time in Networked Control Systems. Modern networking systems often have the capability of sensing and actuating on the environment in an intelligent way. This capability strongly relies on guarantees that the right information at the right place and

at the right time is available to the system for deciding the right action to take. Failure of these guarantees can lead to catastrophic consequences in safety critical applications such as industrial processes control, autonomous navigation, robotics, automatic drug delivery, and so on. For this reason, adopting a proper definition of value of information in a networked control system is of paramount importance for national welfare.

Our study has implications beyond the field of control and and information, in terms of the introduction of new mathematical methods and design tools. In laying a theoretical foundation, we expect to draw novel, synergistic connections between control, information, and real systems. The proposed research will also impact the training of a new generation of students through undergraduate student involvement, graduate mentoring and curriculum development, outreach activities, plans for broadening participation in computing and retention of minority students, and broad dissemination activities.

The importance of delivering the right information at the right place and at the right time has been recognized in the literature of networked control systems and it sparked the introduction of several utility functions including the Age-of-Information and the closely related Value-of-Information and Quality of Information. In this project our objective is to show that universal

measures, such as Age of Information, Value of Information, and Quality of Information, are insufficient to characterize the quality of information in terms of its utility for control of dynamical systems, and we characterize a system-dependent and task-dependent utility metric and describe its applications in the framework of control. On the one side, we consider the information flow

occurring in feedback loops governed by event-triggering control policies. We argue that focusing on event-triggering control will bring key insights on how to provide a definition with an immediate operational significance, which takes into account resolution, timing, reliability constraints, and relates them to the parameters of the system under control. On the other side, we consider a

general, and somewhat more informal definition, that has been adopted in diverse fields such as information economics, risk management, and stochastic programming, and we will cast it in a rigorous control-theoretic framework. This approach is fully compatible with the insights we get from event-triggering control, and generally applicable to networked control systems.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.