Mathematical modeling of the vector control sys-tem of the asynchronous drive of the bridge crane with a fuzzy-controller for the purpose of increasing energy-efficiency

The article solves the current scientific and technical problem of increasing the energy efficiency of the control system for asynchronous electric drives of lifting and transport equipment of enterprises in the engineering industry, in particular overhead cranes, characterized by a high level of dynamic load both in terms of mechanical and electromagnetic indicators. In order to compare the efficiency of control systems, computer modeling of vector control of an asynchronous electric drive was carried out using proportional-integral controllers and neuroregulators based on fuzzy logic. The results of the simulation are presented and the advantages of using a vector control system with a fuzzy neuroregulator in relation to an asynchronous electric drive of an overhead crane are shown, namely, increasing the energy efficiency of operation and reducing dynamic loads during sudden changes in the control signal, ensuring high accuracy of the control process. Goal. Study of the dynamics of an electric drive with a fuzzy controller to achieve improved energy efficiency indicators of material handling equipment. Methodology. An algorithm has been developed for the operation of a vector control system for an asynchronous electric drive of an overhead crane with a fuzzy controller. Computer models of electric drive vector control and vector control subsystems have been developed. A neuroregulator for a vector control system for an asynchronous drive of an overhead crane was synthesized. Results. Mathematical modeling of an electric drive with vector control and the use of proportional-integral and Fuzzy controllers in the electric drive speed loop showed the difference in dynamic modes. A system with a fuzzy controller shows better energy efficiency in transient processes. Power decrease is 15-20%. Conclusions. The simulation results indicate an increase in energy efficiency in transient processes when operating lifting and transport equipment with an asynchronous electric drive. In addition, the use of a fuzzy neuroregulator operating on the basis of Fuzzy logic in the control system makes it possible to create a high-precision asynchronous electric drive with smooth transient processes.