Switched reluctance motor intelligent control system based on WIFI

Abstract

The invention is a switched reluctance motor intelligent control system based on WIFI, which includes a server, a WIFI communication module, a mobile terminal, multiple bottom intelligent switched reluctance motor controllers and multiple switched reluctance motors. Each bottom intelligent switched reluctance motor controller is connected with one switched reluctance motor on the production line,and includes a monitoring module, a drive module, a control module and a WIFI module. The mobile terminal accesses and modifies various functions in the server, and can receive fault warning information. The switched reluctance motors feed back the operation parameters of the switched reluctance motors in real time during normal operation and send the data to the server periodically. The server optimizes and records the operation parameters of the switched reluctance motors according to a lot of received data and a reinforcement learning algorithm, and optimizes and updates the control parameters of the control modules when the collected parameters of the switched reluctance motors deviate from a normal value and reach a safety threshold, so as to better control the operation of the switched reluctance motors.

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 the control parameters of the switched reluctance motor and performing fault warning. Background technique [0002] At present, most industrial applications of switched reluctance motors use PI controllers for control, and the theoretical research directions are mostly complex neural networks and iterative control algorithms. The algorithm is limited and the algorithm is fixed, (such as using an advanced intelligent algorithm, a large amount of storage space is required, and the actual controller used in the factory usually does not adopt a large memory design considering the 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 sys...

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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