Recursive output error identification algorithms theory and evaluation

Several recurisve algorithms for parametric identification of discrete time systems derived from Model Reference Adaptive System (M.R.A.S.) techniques are analysed. All these algorithms belong to the class of output error methods which have been very little discussed previously in the identification literature. These algorithms are analysed in the deterministic and stochastic environment using the Equivalent Feedback Representation (E.F.R.) and Ordinary Differential Equation (O.D.E.) methods respectively. A comparative evaluation of these algorithms is presented. This comparison is made also with respect to various widely used recursive algorithms belonging to the 'equation error method' (extended least squares, approximate maximum likelihood).

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