An Approach to the Implementation of Nonparametric Algorithms for Controlling Multidimensional Processes in a Production Problem

Abstract

In paper, consider nonparametric algorithms for the identification and control of multidimensional discrete-continuous processes that are typical for many practical problems. The main feature of the considered multidimensional systems is the presence in them of stochastic dependences of both input and output variables. Under such conditions, the mathematical description of such objects leads to a system of implicit equations. Nonparametric algorithms for modeling and control for multidimensional systems are proposed, as well as the subsequent implementation of software-based on these algorithms in production. Attention should be paid to the fact that the modeling of such processes is reduced to the search for the predicted values of the output variables for the known input. Moreover, for implicit equations, it is only known that one or another input variable can depend on other input and output variables that determine the state of a multidimensional system. The subsequent control of multidimensional systems is considered in conditions of insufficient a priori information about the object of research. The main component in the control problem is the determination of the reference influences, for the search of which a nonparametric algorithm is used. The essence of this algorithm is to find a common area of intersection of the values of the output variables, which will satisfy all components of the output vector. When implementing software, it is necessary to take into account information security issues, especially for three key tasks: process control, archiving (saving history) of technological parameters and working with alarms. This article provides some guidelines for implementing safeguards for archiving and alarms.