永磁直线同步电机智能分数阶动态面控制  

Intelligent Fractional Order Dynamic Surface Control of Permanent Magnet Linear Synchronous Motor

作　　者：武训 王丽梅[1] WU Xun;WANG Limei(School of Electrical Engineering,Shenyang University of Technology,Shenyang 110870,China)

机构地区：[1]沈阳工业大学电气工程学院,沈阳110870

出　　处：《组合机床与自动化加工技术》2023年第9期116-119,共4页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国家自然科学基金项目(51875366)。

摘　　要：针对永磁直线同步电机(PMLSM)存在的参数变化、外界扰动等不确定因素影响位置跟踪精度的问题,提出一种基于径向基函数(RBF)神经网络的分数阶动态面控制方法。在反步控制器设计的基础上,引入动态面控制技术,避免了反步控制存在的“微分爆炸”问题;在虚拟控制量中加入分数阶微积分项,增加了系统的参数自由度;利用RBF神经网络逼近补偿系统的不确定因素。基于Lyapunov稳定性理论,对所控制的系统进行稳定性分析证明。仿真结果表明,所提出的控制方法能减小系统的跟踪误差,提升鲁棒性,加快系统的响应速度。A fractional order dynamic surface control method based on radial basis function(RBF)neural network is proposed to solve the problem that the position tracking accuracy of permanent magnet linear synchronous motor(PMLSM)is affected by uncertain factors such as parameter variation and external disturbance.Based on the design of backstepping controller,the dynamic surface control technology is introduced to avoid the“differential explosion”problem of backstepping control.The fractional calculus is added to the virtual control variable to increase the degree of freedom of the system parameters.RBF neural network is used to approximate the uncertain factors of the compensation system.Based on Lyapunov stability theory,the stability of the controlled system is proved.The simulation results show that the proposed control method can reduce the tracking error,improve the robustness and accelerate the response speed of the system.

关 键 词：永磁直线同步电机 分数阶动态面控制 RBF神经网络 位置控制 

分 类 号：TH165[机械工程—机械制造及自动化] TG659[金属学及工艺—金属切削加工及机床]