2019
Volume 19, Number 3/4, pp. 96-102
Parameter identification in nonlinear dynamic systems of industrial processes
B. Shanshiashvili and N. Kavlashvili
Georgian Technical University, Tbilisi, Georgia
The problem of parameter identification in 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. A method of parameter identification in the steady state based on observation of the system's input and output variables during sinusoidal input influences is proposed. The solution of the problem of parameter identification is reduced to the solution of systems of algebraic equations by using the Fourier approximation. Parameters are estimated by the least squares method. Reliability of the results in the presence of noise depends on the accuracy of measurement of system output signals and on the mathematical processing of the experimental data.
Keywords: block-oriented model, control, identification, nonlinear system, parameter, sinusoidal