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ADAPTIVE OBSERVER OF STATE VARIABLES OF A NONLINEAR NONSTATIONARY SYSTEM WITH UNKNOWN CONSTANT PARAMETERS

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For a nonlinear nonstationary system an adaptive state vector observer using output variable measurement is developed the control matrix (vector) and the nonlinear component of the equation of state of the system contain unknown constant parameters. When synthesizing the observer, a preliminary parametrization of the original nonlinear system is carried out. Then the derived system is reduced to a linear regression model. At the next stage, unknown constant regression parameters are estimated using the least squares method with a forgetting factor. The result of the previous work by the authors, which considered a linear non-stationary system containing unknown parameters in the control matrix (vector), is extended to the case when the equation of state of the system contains a partially unknown nonlinearity. The performance of the proposed algorithm is illustrated by mathematical modeling.

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