直线电机迭代学习控制非重复性扰动抑制研究

Iterative Learning Control of Linear Motor for Non-repetitive Disturbance Suppression

针对直线电机迭代学习控制过程中非重复性扰动积累问题,提出了将干扰观测器和小波变换相结合的抑制非重复性扰动的算法。首先分析了扰动对迭代学习控制跟踪误差的影响,包括负载扰动和测量噪声,给出了干扰观测器和小波滤波抑制迭代学习控制中非重复性扰动的理论依据。干扰观测器直接对干扰估计并进行补偿,在时间域上抑制非重复性扰动,小波变换可分离出非重复性扰动,重构出不含非重复性扰动的误差信号,在迭代域上抑制了非重复性扰动的积累。利用辨识出的直线电机平台模型进行仿真,仿真结果证明提出的策略能够减少前馈控制信号中非重复性扰动积累,减小迭代学习控制收敛误差。

Iterative learning control(ILC)algorithm based on disturbance observer and wavelet transform is proposed for the non-repetitive disturbance amplification in ILC for permanent magnet linear motor.In this paper,analysis of the tracking error of ILC shows the influence of non-repetitive disturbance,including load disturbance and measurement noise,which is the theoretical basis of disturbance observer and wavelet filter in suppressing non-repetitive disturbance.Disturbance observer directly compensates for disturbance,suppressing the non-repetitive in time domain.Wavelet filter identifies and removes the non-repetitive disturbances,then reconstructs the error signal,suppressing the non-repetitive disturbance in iteration domain.Simulation results of the linear motor show that a better tracking performance is obtained together with a feedforward signal that significantly lessen non-repetitive disturbances.