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The design of optimal control architectures and the optimal selection of controlled variables represents a critical task for maximizing the economic profitability of operating plants. Traditionally, controlled variables are selected based on heuristics or past experiences. For cyber-physical systems (CPS), where physical and virtual components can be integrated in the same unit to evaluate the dynamic response of innovative power cycles past experiences may not be available. Trial-and-error methods can be time-consuming and costly. Besides, the selected controlled variables may not be optimal from the economic perspective. A systematic approach to the selection of controlled variable for cyber physical systems is presented here. The method is applied to a solid oxide fuel cell (SOFC)-gas turbine (GT) CPS at the National Energy Technology Laboratory (NETL) in Morgantown, WV. The main result of this work is the synthesis of optimal controlled variable sets for a cyber physical system exhibiting trade offs between economics as well as controllolability of variables.

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