PARAMETER IDENTIFICATION OF NONLINEAR DYNAMIC SYSTEMS OF INDUSTRIAL PROCESSES

Abstract

The problem of parameter identification of nonlinear dynamic systems of industrial processes on the set of continuous block-oriented models, the elements of which are different modifications of the Hammerstein and Wiener models, is considered. Method of parameter identification in steady state based on the observation of the system's input and output variables at the input sinusoidal influences is proposed. The solution of the problem of parameter identification is reduced to the solution of the systems of algebraic equations by using the Fourier approximation. The parameters’ estimations are received by the least squares method. Reliability of the received results, at the parameter identification of
the nonlinear system in industrial conditions at the presence of noise depends on the accuracy of the measurement of system output signals and mathematical processing of the experimental data at the approximation.