Self-constructed T-S type fuzzy neural network control method of permanent magnet synchronous motor

The invention discloses a self-constructed T-S type fuzzy neural network PID controller which is used for controlling the rotating speed of a permanent magnet synchronous motor (PMSM). A self-constructed fuzzy neural network determines whether to carry out structure learning or not by judging degree...

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Bibliographic Details
Main Authors CAI SONGCHANG, KANG ERLIANG
Format Patent
LanguageChinese
English
Published 25.02.2022
Subjects
CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORSOR DYNAMO-ELECTRIC CONVERTERS
CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
ELECTRICITY
GENERATION
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Summary:The invention discloses a self-constructed T-S type fuzzy neural network PID controller which is used for controlling the rotating speed of a permanent magnet synchronous motor (PMSM). A self-constructed fuzzy neural network determines whether to carry out structure learning or not by judging degree quantity and similarity and carries out parameter learning based on a gradient descent method, and the two processes are carried out on line at the same time. The fuzzy neural network of the T-S type structure is simpler in calculation and beneficial to mathematical analysis. Jacobian information of a control system can be obtained through an RBF neural network identifier and transmitted to the fuzzy neural network controller to adjust PID parameters online in real time, so that the control system of the permanent magnet synchronous motor has better anti-interference capability and dynamic performance. 本发明公开了一种自构式T-S型模糊神经网络PID控制器来控制永磁同步电机(PMSM)的转速，自构式模糊神经网络通过对程度量和相似度的判断决定是否进行结构学习，基于梯度下降法进行参数学习，二者是同时在线进行的。T-S型结构的模糊
Bibliography:Application Number: CN202111472892