基于复合神经网络重构对象的永磁同步直线电机变参数型位移速度并行控制  

Parallel Displacement Velocity Control of Permanent Magnet Synchronous Linear Motor with Variable Parameters Based on Composite Neural Network Reconstruction Object

作　　者：鲍明堃 周扬忠 Bao Mingkun;Zhou Yangzhong(Fujian Key Laboratory of New Energy Generation and Power Conversion Fuzhou University,Fuzhou 350116 China)

机构地区：[1]福州大学福建省新能源发电与电能变换重点实验室,福州350116

出　　处：《电工技术学报》2024年第8期2470-2484,共15页Transactions of China Electrotechnical Society

基　　金：福建省自然科学基金资助项目(2021J02023)。

摘　　要：针对永磁同步直线伺服电机(PMSLM)传统位移控制算法中控制器系数固定带来的控制精度不足等问题,提出一种基于复合神经网络重构对象的PMSLM变参数型位移速度并行控制策略。首先,利用动子位移、线速度的误差信息设计变参数并行控制器;其次,建立含有控制对象多维信息的复合径向基神经网络观测动子位移,并得到控制对象的偏导信息;再次,基于闭环稳定条件,以周期检索的误差与控制目标的比较结果为基础,构建完整的位移速度并行控制器参数更新策略;最后,实验结果表明,该文所提控制策略能实现不同给定位移的高精度控制,且具有控制不同对象参数的泛用性。A permanent magnet synchronous linear servo motor has the characteristics of high thrust density,high efficiency,and fast control response.It is widely used in rail transit,intelligent manufacturing,and aerospace fields.The electrical or mechanical parameters of the motor and nonlinear resistance interference will affect the high precision control of the linear servo.Therefore,the stable and efficient displacement control algorithm has important engineering application value to improve the system performance.Servo control can be divided into serial and parallel systems according to the relative position of displacement and velocity loop.However,whether serial or parallel control,most controller parameters need to be set in advance and are generally fixed,and adjusting the actual control effect is impossible.This paper proposes a parallel control strategy of variable parameter displacement velocity of permanent magnet synchronous linear motor based on composite neural network reconstruction object,which realizes the high-performance control of linear servo motor.Firstly,a parallel controller with variable parameters is designed using the error information of the moving displacement and linear velocity.Then,the displacement output of the permanent magnet synchronous linear motor is reconstructed by a composite radial basis neural network containing multi-dimensional information of the control object,and the partial derivative of the displacement to the control signal is obtained.Finally,based on the closed-loop stability condition of the system,a complete parameter update strategy of parallel controller with displacement velocity is provided according to the comparison between periodic retrieval errors and control targets.In the experiment,a permanent magnet synchronous linear servo system is designed,and different network observations,position controls,and object parameter controls are compared.The network comparison shows that the composite radial-based neural network has fast observation speed and high observati

关 键 词：永磁同步直线电机 并行控制 复合径向基神经网络 变参数 更新机制 

分 类 号：TM359.4[电气工程—电机]