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ALGORITHM OF ADAPTIVE ESTIMATION OF PARAMETERS FOR A CLASS OF NONLINEAR NON-STATIONARY SYSTEMS

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The problem of identification of unknown parameters for a class of non-stationary nonlinear systems is considered. It is assumed that non-stationary parameters can be represented as outputs of linear generators with unknown state matrices and initial conditions. The system state variables are supposed to be available for measurement. At the first step of the developed algorithm, the problem of parametrization of the initial dynamic model is solved to obtain a linear static regression model. At the second step of the algorithm, the unknown constant parameters of the linear regression model are estimated. Then the synthesis of observers for non-stationary parameters is performed. Presented results of computer simulation demonstrate the proposed algorithm efficiency.

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