摘要
为实现无速度传感器直接转矩控制,有时采用神经网络转速辨识器,但前馈神经网络结构难以确定,运用BP算法时又极易陷入局部解。将人工鱼群算法与BP算法相结合的AFSA+BP算法,实现了人工鱼群算法的全局搜索能力与BP算法的局部寻优性能的互补结合。将所设计的神经网络转速辨识器运用到直接转矩控制系统当中,利用Matlab/Simulink实现无速度传感器控制系统的仿真实验结果表明,该算法具有良好辨识效果。
To achieve speed-sensorless direct torque control (DTC) system, neural network (NN) was ap- plied to design speed identifier. But, feed forward network is difficult to confirm the structure and BP algo- rithm is easy to plunge into local solution. To combine AFSA with BP, which is called AFSA +BP algorithm and it realized the combination of AFSA's global search capability and BP algorithm's local optimize perform- ance. The performance of the proposed scheme was carried out by simulation experiment using Matlab/Simu- link.
出处
《电气传动》
北大核心
2009年第3期3-6,17,共5页
Electric Drive
基金
辽宁省自然科学基金资助项目(20032032)
教育部“春晖计划”合作科研项目(Z2005-2-11008)
辽宁省教育厅高校科研项目(20206331)
关键词
人工鱼群算法
神经网络
直接转矩控制系统
artificial fish school algorithm
neural network (NN)
direet torque control (DTC)