Models of open-loop and closed-loop systems for automatic control of air supply to a steam boiler are constructed. An open-loop system is modeled and, on its basis, a closed-loop system with a PI controller tuned to the optimum modulo is developed. The introduction of a frequency converter into the control system for more economical and gentle operation of the fan electric drive is considered. The developed system consists of models of a controller, a frequency converter, an asynchronous motor and a blower fan. The simulation results are presented, demonstrating the operability of the resulting system in compliance with the requirements for stability and speed. The modernized closed system has a number of advantages over the existing open one, and the described method of its construction can be applied when implemented at enterprises using air blowers.

Keywords: automatic pressure control system, automatic control system, closed system, open system, PI controller, modular optimum

A set of data on potentially dangerous asteroids for the Earth is analyzed. According to descriptive statistics, a preliminary analysis and data processing is performed. The correlation between the parameters allows you to identify those that will be used to train the models. With the help of machine learning models, asteroids from the database are classified into hazardous and non-hazardous. Methods of logistic regression, k-nearest neighbors; decision tree and others are used. Using cross-validation, the best method is found, then its optimal hyperparameters are determined. The quality of the classifier model is evaluated by the metrics of completeness (Recall) and its standard deviation, as well as using the error matrix (confusion matrix) and the average absolute error in percent (MAPE). The results of analysis and modeling in Python are presented, demonstrating the high accuracy of predicting the resulting model.

Keywords: machine learning, predictive model, data analysis, imbalanced data, logistic regression, k-nearest neighbors, decision tree, random forest, support vector machine, cross-validation

The tasks of preparing for the modernization of the automatic pressure control system with the transition from the use of a PD controller in favor of a PID controller and the introduction of a controlled electric fan drive in a boiler plant are being solved. A technique for constructing a fan model in the automatic control system for air supply to the boiler is given using the example of a VD-18 blower fan and a BKZ-160 boiler. The block diagram of the operation of the fan and pipeline is given. A mathematical model of the fan is shown, a calculation is made and a computer model is designed in MATLAB Simulink. The simulation results are presented, which prove the correctness of the obtained model. The presented model can serve as a basis for automating the air supply system in other boilers using blowers.

Keywords: automatic pressure control system, automatic control system, dynamic model, computer model, blower fan, boiler plant