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Professor John Baras (ECE/ISR) is the principal investigator for "The Value of Information in Networked Control: A Utility Based Approach," a four-year, $275K National Science Foundation collaborative research award that addresses the problem of determining the quality or value of 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.
This study will introduce new mathematical methods and design tools that will have implications beyond the fields of control and information. In laying a theoretical foundation, the researchers expect to draw novel, synergistic connections between control, information, and real systems.
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 sparked the introduction of several utility functions including "Age of Information" and the closely related "Value of Information" and "Quality of Information." This project will show that these universal measures are insufficient to characterize the utility of quality of information for control of dynamical systems. The researchers will characterize a system-dependent and task-dependent utility metric and describe its applications in the framework of control.
The researchers will consider information flow occurring in feedback loops governed by event-triggering control policies. They will argue that focusing on event-triggering control will bring key insights on how to provide a definition with an immediate operational significance. This will take into account resolution, timing, reliability constraints, and relate them to the parameters of the system under control. The researchers also will consider a general, and somewhat more informal definition that has been adopted in diverse fields such as information economics, risk management, and stochastic programming. Theywill cast it in a rigorous control-theoretic framework. This approach is fully compatible with insights from event-triggering control, and is generally applicable to networked control systems.
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