ДИНАМИЧЕСКАЯ ИДЕНТИФИКАЦИЯ ПАРАМЕТРОВ СХЕМЫ ЗАМЕЩЕНИЯ АСИНХРОННОГО ДВИГАТЕЛЯ НА ОСНОВЕ БАЛАНСА МГНОВЕННОЙ ПОЛНОЙ МОЩНОСТИ В УСТАНОВИВШЕМСЯ РЕЖИМЕ

Abstract

The relevance Automated electric drive (AED) is one of the most important and most common control objects in automatic process control systems (ACS). The control of the output coordinate in the AED, for the implementation of feedback with an automated process control system, can be carried out both with the help of a speed sensor and without it, using the computing power of a frequency converter included in the AED. For the sensorless AED to work in an automated process control system, it is necessary to ensure adequate restoration of the vector of state variables of the induction motor (IM) in the frequency converter using a configurable mathematical model. To restore the vector of state variables, it is necessary to select coefficients in the system of differential equations that correspond with some error to the electrical parameters of the BP replacement circuit, i.e. to carry out the identification procedure. In fact, the procedure for determining the parameters of the PS is the process of finding the extremum of the objective function, built on the basis of data obtained during the operation of the PS. In electrical engineering, numerical methods for finding the extremum of the objective function have become widely used to identify parameters, but these methods have significant limitations and disadvantages. The problem of using numerical methods to find the extremum of an objective function with two or more arguments in AED microprocessor control systems is that it is necessary to calculate partial derivatives in discrete form for each argument of the function. Calculation of partial derivatives in ideal systems without noise and disturbances is a proven and easy-to-implement process, but noise and disturbances are present in real microprocessor systems. Because of this, when calculating partial derivatives for each argument, the probability of breakpoints of the first and second kind increases, the struggle with which presents a certain difficulty. One of the classes of methods that allow determining the extremum of an objective function without finding partial derivatives are metaheuristic algorithms, and in particular genetic algorithms. Aim of research Experimental study of the efficiency of a genetic algorithm in the problem of dynamic identification of parameters of an induction motor circuit with an open rotor winding without stopping and decommissioning an electrical complex. Research methods Metaheuristic algorithms, iterative procedures, genetic algorithm, discrete systems, optimization methods. Results The effectiveness of the genetic algorithm was experimentally tested and proved in the problem of dynamic identification of parameters of the induction motor replacement circuit with an open rotor winding without stopping and decommissioning the electrical complex.