Design and adaptive setting of dynamic process prognostication functions in variables gains for models with multirate discretization

Abstract

Theoretical concepts are considered concerning design and adaptive setting of output coordinates of prognostication functions of dynamic processes, which are represented as time series mathematical models under discretization of the input disturbances with small periods of sampling and output coordinates with large ones. The input disturbances are nonmeasurable and have the mean value differing from zero in the time intervals conforming to the process inertia. The designed prognostication function is represented in the form of input coordinates gains and control responses under discretizationt of them with large periods of sampling.