数控机床直线伺服系统智能反推控制的研究

针对高速高精数控机床直线伺服系统,考虑参数变化、外部负载扰动和摩擦力等不确定因素对系统伺服性能的影响,设计基于递归模糊神经网络( RFNN)的反推控制器,利用了递归神经网络具有捕获系统动态信息的优点,可实时补偿不确定因素对跟踪性能的影响.仿真结果表明,该控制策略明显降低了不确定因素对系统性能的影响,从而显著提高了直线伺服系统的位置跟踪精度.

Study on Intelligent Backstepping for Linear Servo System of NC Machine Tool

In view of high speed and precise NC machine tool droved by linear servo systems,an adaptive backstepping sliding mode controller(ABSMC) was proposed considering the influence of the lumped uncertainties with parameter variations,external force disturbances and frictions for linear servo systems.,an intelligence backstepping control is introduced to suppress further the tracking error.Considering the influence of the lumped uncertainties with parameter variations,external force disturbances and frictions for PMLSM,a backstepping controller based on recurrent neural network is designed.The advantages of recurrent neural network with capturing the dynamic information of system are used,can compensate real time the influence of tracking performance.Simulation results show that the proposed algorithm can reduce effectively the influence of the lumped uncertainties on system performances.The tracking performances of the PMLSM servo system are significantly improved.