新型智能PID控制的PMLSM调速系统研究  

Research of Speed Regulating System Based on New Intelligent PID Control

作　　者：王辉[1] 张段芹[1] 王才东[1] 

机构地区：[1]郑州轻工业学院机电工程学院,郑州450002

出　　处：《微电机》2014年第1期71-76,共6页Micromotors

基　　金：国家科技支撑计划资助项目(2012BAF12B13);河南省重点科技攻关项目(132102110057);郑州市科技攻关项目(131PPTGG411-3);郑州轻工业学院博士科研基金支助项目(000346)

摘　　要：为进一步提高永磁直线电机调速系统的动静态性能,提出将BP神经网络与传统PID控制器相结合,以实现PID参数的最优化自整定。在研究常规BP神经网络的控制算法的基础上,对常规BP算法的学习速率和动量因子不能动态调整带来的缺陷进行分析,提出基于误差变化率的动态调整算法,实现对PID控制器参数的自寻优,并将算法应用于永磁直线电机矢量控制系统速度调节器中。仿真实验结果表明,改进后的基于BP神经网络PID控制算法与传统PI控制器相比,控制系统的动静态性能更优,稳定性更好,解决了由于参数整定困难而导致PID控制器性能不能达到最优化的问题。In order to further improve on the static and dynamic performance of the permanent magnet linear synchronous motor speed regulating system, the traditional PID controller was combined with the BP neural network to achieve PID parameters self rate and the momentum factor about the regulating to optimize the parameters. The defects that the learning normal BP neural network can＇t regulate dynamically leads to were analysed on the basis of studying the normal BP neural network algorithms, and the dynamic regulating algo- rithm based on error variety-rate was proposed to realize to the self-optimization of the PID parameters, and it was applied to the permanent magnet linear synchronous motor to control the motor speed. The simulation re- suits prove the PID controller combined with the improved BP neural network has better static and dynamic performances and stability, and resolved the problems which the traditional PID controller can＇t achieve the most optimization because of the difficulty of the parameter regulating.

关 键 词：永磁直线同步电机 PID控制 BP神经网络 动态调整 

分 类 号：TM341[电气工程—电机] TM359.4