Nonlinear Model of a Stochastic Control System

Abstract

In this work, a model of a stochastic control system is obtained based on the method of canonical expansions of random processes. The algorithm for calculating the parameters of the system allows one to take into account an arbitrary order of nonlinear links and the amount of a posteriori information about the studied sequence of changing the coordinates of the control object. The mathematical model also does not impose any restrictions on the behavior properties of the controlled object: Linearity, stationarity, monotonicity, scalarity, Markov property, etc. The paper presents a block diagram of an algorithm for calculating the parameters of a stochastic control system. The formula for the mean square of the extrapolation error of the future coordinates of the object under study allows us to estimate the accuracy of the solution to the control problem.