Kybernetika

Problem of parametrization of multi-output autoregressive regressive Gaussian model (ARX) is studied in the context of prior design of adaptive controllers.

The substantial role of prior distribution of unknown parameters on the parametrization is demonstrated. Among several parametrizations a nontraditional one is advocated which \begin{itemize} \vspace*{-1.7mm} \item[--] makes it possible to model the system output entrywise, thus it is very flexible; \vspace*{-1.7mm} \item[--] models relations among system outputs in a realistic way; \vspace*{-1.7mm} \item[--] is computationally cheap; \vspace*{-1.7mm} \item[--] adds an acceptable amount of redundant parameters comparing to the most general but computationally most demanding parametrization which organizes the unknown regression coefficients in column vector. \end{itemize} \vspace*{.7mm}