基于新型转子磁链辨识方法的多电机系统同步控制

磁链观测是多电机闭环控制系统性能的重要环节,而电机参数的变动通常使磁链观测的精度难以满足要求.针对3台异步电机和3台逆变器组成的三电机同步系统,提出了局部模型网络磁链辨识方法.将电机参数变化当作干扰项来处理,解决了因电机参数变动影响磁链准确观测的难题.在此基础上,采用神经网络逆构建由速度、磁链、张力子系统组成的伪线性复合系统,实现了三电机同步系统中速度、磁链和张力的解耦.分别对各子系统设计线性闭环控制器,实现了三电机系统的同步控制.仿真结果验证了磁链辨识的准确性和控制系统良好的动静态性能.

Decoupling control of multi-motor synchronous based on new rotor fluxobserver

Rotor flux observation accuracy is a key factor to affect control performance of multi-motor closed-loop system
working on rotor flux field-oriented vector control mode, but the precision of flux observation is usually difficult to meet
the requirement because of motor parameters variation. Aiming at three-motor synchronous system, the model of rotor flux
is built based on local model network. In this model, variability of machine parameter is taken as interference term, so the
accuracy of flux identification is improved. Then, based on the neural network inverse control method, linear subsystems of
speed, rotor flux linkage and tension can be obtained by combing the inverse neural network with the three-motor synchronous
system. Thus, the speed, flux and tension control of three-motor system can be decoupled. The simulation results show that
the flux model has satisfactory accuracy, and control system has good dynamic and static operation performance.