机床直线同步电机理想控制器设计及仿真分析

Design and Simulation Analysis on Ideal Controller of Linear Synchronous Motor for Machine Tool

将非线性磁悬浮系统作为研究对象,建立合适的误差函数,在逼近过程中合理利用RBF神经网络,制定自适应律,该控制方法能够大大加强整个系统的抗干扰性。并开展仿真研究。突加负载下,NNDAC控制恢复所需的时间为0.068、动态降落为1.2×10^(-5)m;相较于SMC和PID控制恢复速度依次提升38.2%、77.3%,动态降落依次下降64.7%、76%NNDAC有效降低悬浮高度的变化幅度,增强其抗干扰性。模拟端部效应扰动下,NNDAC控制曲线几乎没有任何波动,且相较于SMC和PID控制其动态降落分别减小85.7%与95%,NNDAC控制有利于平缓气隙高度的波动,加强系统的抗干扰性。

Taking the nonlinear magnetic levitation system as a research object,this paper establishes the appropriate error function,and rationally adopts the RBF neural network in the process of approximation to formulate the adaptive law.This control method can greatly strengthen the anti-interference performance of the whole system and carry out the simulation research.Under sudden load,the time required for the control and recovery of NNDAC is 0.068,and the dynamic fall is 1.2 × 10~(-5) m.The control recovery speed of NNDAC respectively increases by 38.2% and 77.3% compared with SMC and PID,and the dynamic fall respectively decreases by 64.7% and 76%.NNDAC effectively reduces the variation amplitude of hoverheight and enhances anti-interference performance.Under the simulated end-effect disturbance,NNDAC control curve has almost no fluctuation,and its dynamic fall respectively decreases by85.7% and 95% compared with SMC and PID control.NNDAC control is beneficial to smooth the fluctuation of air-gap height and enhance the anti-interference performance of the system.