OPTIMAL MEASUREMENT COMBINATIONS AS CONTROLLED VARIABLES

Abstract Self-optimizing control is a promising method for finding appropriate controlled variables. Recently, locally optimal methods were introduced for finding controlled variables by minimizing the worst-case loss. In this paper, we extend these local methods for average-case loss minimization. Furthermore, we present a method for finding optimal combinations of measurements for local self-optimizing control, for both of worst- and average-case loss minimization. The proposed results find the optimal solution efficiently, as compared to the available techniques like non-linear optimization or null space method. The usefulness of the results is demonstrated using an evaporator case study.