Controllers Synthesis for Computer Research of Dynamic Conveyor Belt Model Using Intelligent Algorithms

Abstract

This paper is devoted to the synthesis and analysis of such a controlled model of a belt conveyor with switching modes of operation, which takes into account the axial resistance and the dynamic change in the angle between the horizontal plane and the plane of the conveyor belt. The problems of constructing a neural network controller and a PID controller for studying the model are considered. The solution of optimal control problems with the use of constructed controllers is proposed. The results of computer experiments on the study of trajectory dynamics are presented. The implementation of the proposed algorithms for constructing trajectories and intelligent control is carried out using the Python language and the corresponding mathematical libraries. The synthesis of control laws for stabilizing the elevation angle of the conveyor belt is carried out taking into account the variable mass of the loads, as well as taking into account the change in the center of mass of the conveyor. Qualitative effects that arise due to axial resistance are studied. The questions of the adaptability of neural network control and PID control in relation to a linear increase in axial resistance are considered. A comparative analysis of computational experiments with the use of various types of regulators is carried out. The obtained results can be applied to the design of new control systems for production lines, as well as in the stabilization of dynamic controlled models. The considered method of estimating the influence of axial resistance on the trajectory dynamics can be used in the study of various generalized models of conveyor transport control. The developed software is aimed at being used as part of a software package for modeling conveyor transport systems with intelligent control #CSOC1120.