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Industrial Automatic Control Systems and Controllers

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Statistical Identifi cation. Advanced Algorithms for Adaptive Filtering
V.I. Kuznetsov

The paper deals with the application of advanced adaptive fi ltering algorithms in problems of joint estimation of states and parameters identifi cation of dynamical systems, based on the extension of the model states and dimensions depending on the current situation of information: the initial states of dynamical systems and acting in the course of their operation disturbances. Represented by discrete state model and measurements manifestation Markov noise component forming the
equation of state, the manifestation of a Markov random noise in the measurement equation, as well as a joint manifestation
Markov forming part of the noise in the equation of state and Markov random noise in the measurement equation. The criteria
and conditions for the application of advanced adaptive fi ltering algorithms based on an assessment of the probability measure
of signifi cance whitewash coordinates of the selected mathematical model states in the realized experimental conditions.
Keywords: signifi cance; identifi cation; model; estimate; parameter; error; condition; fi ltering.

Contacts: E-mail: vi_kuznetsov@bk.ru

Pp. 23-28.

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