Earning Criteria

• Badge earners complete SE-5202 Cyber-Physical Control Systems course at the University of Connecticut, which is a hybrid-online graduate course that can be taken from anywhere in the world. Earners can take this graduate course as a matriculated UConn graduate student or as a non-degree graduate student, which does not require admission to the UConn graduate school. Badge holders complete a course-long project and must earn a B- or better on this project to earn the badge.
• Badge earners can create and update CPS models using real-time operating data, conduct modeling practices for physical and computational processes of CPS, design techniques for stability and safety, among other specifications for CPS, model and implement control systems, and describe and characterize uncertainty, statistical inference, detection, and estimation in models and analyze their effects on CPS behavior. See Standard [1] NAE-CPS below.
• Badge earners can develop and use systematic mathematical approaches for constructing nonlinear empirical models informed by physics principles, and develop and use mathematically rigorous frameworks and efficient, robust numerical methods for data assimilation into models of complex systems that are informed by numerical analysis-based error estimates for simulations and statistics-based error estimates for the assimilated data. See Standard [2] DOE-SIAM below.
• Badge earners can incorporate observational and empirical data to model and simulate a complex system, quantify the effects of uncertainty on predictions using complex models and when fitting complex models to observations and perform modeling and analysis to design, quantify and predict uncertainty in behavior in a complex system and analysis to design and predict operating characteristics for a complex system. See Standard [2] DOE-SIAM below.
• Badge earner can describe the characteristics of good quality requirements for control and provide examples, interpret and use outcomes of modeling and analysis for control system design, explains why there is a need for functional models of the system, use analysis techniques to support an architectural design process, and use verification and validation to establish whether a system meets requirements. See Standard [3] INCOSE ISECF below.
• The project aims to develop skills that badge earners can describe a system of interest to control, the existing best practice for control, and how a control design is expected to improve its performance. They develop a model for the chosen system, perform open-loop analysis, and design a classical control system. Badge earners then design an optimal or robust and adaptive or non-linear control system for the same system and demonstrate its performance improvement over classical control.