Non-parametric identification and control algorithms for T-processes

In this paper, nonparametric identification and control methods are considered for multidimensional discrete-continuous processes with a delay inherent in many real productions. Such systems are typical for practice, including in the rocket and space industry, as well as in the technological processes of space technology production. Considering multidimensional processes, it is necessary to take into account the relationships between input and output variables, as well as their relationships with each other. Moreover, these connections are not always known to the researcher. When taking into account unknown connections of input variables, the researcher will deal with tubular processes or H-models, and when taking into account unknown connections of output variables, the model for one or another channel of the object will be analogs of implicit functions. In general, the model of a multidimensional object will be represented as a system of nonlinear implicit equations. In this case, the solution of the identification problem will be reduced to finding the prediction of the vector of output variables from the known values of the vector of input variables and can be obtained only as a result of solving the corresponding system of equations, which were called T-models. The solution of a system of nonlinear implicit equations by parametric identification methods will not lead to the desired result due to the lack of sufficient a priori information, and here there is a need for the use of nonparametric identification methods, as well as the use of system analysis methods. A priori information in the tasks of nonparametric statistics is insufficient, which conventional identification methods cannot cope with. When controlling multidimensional processes, it is necessary to take into account the dependencies of output variables, in connection with which another important feature arises, namely: random values from the domain of determining output variables cannot be used as setting influences; they must be selected from their common intersection.