Identification of parameters of interval nonlinear models of static systems using multidimensional optimization
The article proposes an approach to parametric identification of interval nonlinear models of static systems based on the standard problem of minimizing the root mean square deviation between the values of the modeled characteristics of the static object and the values belonging to the experimental intervals.