On some LS-method modification for parameter estimating of discrete dynamic models. Andrey Nikitenko

Abstract. The simple and widely used method of identification of discrete dynamic models is based on approximation of dynamic equation at each discrete time point. In case of linear by parameters model this leads to well-known LS-method. In contrary to regression problems MLS estimation of parameters leads to displaced values. This work suggests two modifications of LS-method that decrease the displacement in parameter estimations. Suggested methods give significant improvements in parameter estimations, so that they can be used not only as initial values for sophisticated methods, but by themselves (in cases, that do not need extremely high precise). One of this methods is based on integrating of difference equations on "sliding interval" therefore the question of influence of "sliding interval" length on method accuracy is investigated.

Keywords. Discrete dynamic model, identification, parameter estimation, integrating on sliding interval.

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