摘要
研究永磁同步电动机的转速控制问题.对于参数不确定,输出受限的永磁同步电动机系统,提出转速跟踪控制方法.利用神经网络逼近电动机系统中的复杂非线性函数,采用自适应控制,动态面控制技术,设计控制器实现电动机的转速跟踪控制器.文中提出的控制策略不仅能够克服电机参数的不确定性和负载扰动,而且避免了传统反步设计方法存在的"复杂性爆炸"问题.基于Lyapunov稳定性理论,证明闭环系统具有半全局稳定性,转速跟踪误差收敛于原点的极小邻域内.仿真结果验证了所提控制方法的有效性.
This paper considers the speed tracking control of permanent magnet synchronous motors.A speed tracking control method is proposed for permanent magnet synchronous motors with parameter uncertainties.Neural networks are utilized to approximate the complex nonlinear functions.Combining neural networks and dynamic surface control technique,speed tracking controller is developed to guarantee the speed tracking performance in the presence of parameter uncertainties and load torque disturbances.In addition,the presented control scheme can overcome the problem of ＂explosion of complexity＂.Based on Lyapunov stability theory,the closedloop system is semi-globally uniformly ultimately bounded,and the speed tracking error converges to a small neighborhood of the origin.Simulation results verify the validity of the proposed control method.
出处
《系统科学与数学》
CSCD
北大核心
2015年第9期1028-1036,共9页
Journal of Systems Science and Mathematical Sciences
基金
辽宁省教育厅科学研究一般项目(L2013244
L2014244)
辽宁工业大学教师科研启动基金(X201313)资助课题
关键词
永磁同步电动机
输出受限
转速跟踪控制
神经网络控制
动态面控制
Permanent magnet synchronous motor
output constrained
speed tracking control
neural networks control
dynamic surface control
