An intelligent control system of switched reluctance motor based on wifi

Abstract

The present invention is a WIFI-based switched reluctance motor intelligent control system. The system includes a server, a WIFI communication module, a mobile terminal, a plurality of underlying intelligent switched reluctance motor controllers, and a plurality of switched reluctance motors. Each underlying intelligent The switched reluctance motor controller is connected to a switched reluctance motor on the production line, including a monitoring module, a driving module, a control module, and a WIFI module; the mobile terminal can access and modify various functions in the server, and can receive fault warning information . Multiple switched reluctance motors feed back the operating parameters of switched reluctance motors in real time during normal operation, and periodically send the data to the server; the server optimizes the control parameters of switched reluctance motors using a large amount of received data combined with reinforcement learning algorithms. Record, and optimize and update the control parameters of the control module when the collected switched reluctance motor parameters deviate from the normal value and reach the safety threshold, so as to better control the operation of the switched reluctance motor.

Description

technical field [0001] The invention relates to the field of switched reluctance motor control systems, in particular to a novel switched reluctance motor intelligent control system capable of remotely upgrading switch reluctance motor control parameters and performing fault early warning. Background technique [0002] At present, most industrial applications of switched reluctance motors are controlled by PI controllers, and the theoretical research directions are mostly complex neural networks and iterative control algorithms. Limited and fixed algorithm, (such as using advanced intelligent algorithm requires a lot of storage space, the controller actually used in the factory usually does not use large memory design considering cost and durability issues, resulting in few practical application algorithms to choose from) Online monitoring Not realistic with real-time self-adjustment. At present, most of the control systems for switched reluctance motors do not modify the c...

AI Technical Summary

Problems solved by technology

The disadvantage is that the upper computer is not responsible for updating the control parameters of the lower computer, and cannot regularly adjust the motor control effect. At the same time, it lacks fault warning and can only report in time when a fault is detected.

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