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Industrial Automatic Control Systems and Controllers

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Statistical Identifi cation. The Expediency of Linear Maps Nonlinear Measurement Models
V.I. Kuznetsov

The paper investigated the feasibility of a linear mapping of nonlinear models of measurement of output parameters of dynamical systems
for those situations where permissible error formalization models states. Is the formal communication errors formalization state model
with statistically as averaging variations of the measured parameters outputs for advanced linear and nonlinear models of measurement.
It is proved that an appropriate transition to the advanced state model and a linear mapping of nonlinear models of measurement in joint
estimation of states and parameters identifi cation of dynamic systems in cases where the permitted error formalization used models or states
it is necessary the use of adaptive nonlinear fi ltering.
Keywords: adaptation; measure; model; compensation; evaluation; parameter; error; noise; condition; fi ltration.

Contacts: E-mail: vi_kuznetsov@bk.ru

Pp. 30-32.

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