Abstract
In this article, we present an algorithm leading to an optimal controller gain for the automatic regulation of a linear system (closed-loop policy) and to an optimal auxiliary input. This is used for the purpose of either system identification, resulting in the maximum sensitivity measure and thus increased accuracy (Refs. 1–25), or system sensitivity reduction, resulting in the minimum sensitivity measure and thus reliable operation (Refs. 26–46). These results, which are robust in terms of parameter variations, are developed without constraints on the input functions.
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