双直线电机TSKRFNN交叉耦合同步控制研究

Cross-coupled Synchronization Control of Dual Linear Motor Based on TSK-type Recurrent Fuzzy Neural Network

针对高精密龙门移动式镗铣床加工中心X轴的两台直线电机的同步跟踪问题,采用一种TSK型递归模糊神经网络(TSKRFNN)与交叉耦合控制(CCC)相结合的控制方法。利用TSKRFNN解决单轴PMLSM受到参数变化和外界扰动等不确定性影响的问题,估计并补偿总不确定性因素并在线调整网络参数,从而抵抗外界干扰,提高系统的鲁棒性和跟踪性。其次,为解决双直线电机运行时存在的参数不匹配性和耦合问题,将CCC与TSKRFNN相结合,CCC可以将单轴跟踪误差按照一定比例分配给两台永磁直线同步电动机(PMLSM),以抑制由不同步问题引起的不平衡转矩,从而使系统高精度同步运行。最后,通过双直线电机平台证明所提方法的有效性。实验结果表明,该方法鲁棒性及跟踪性优良,可以较好地满足加工中心同步控制的要求。

Aiming at the asynchronous position of dual linear motors on X axis of high precision gantry moving machining centers,a control method combining TSK-type recurrent fuzzy neural network(TSKRFNN)and crosscoupled control(CCC)was adopted.TSKRFNN was used to solve the problem that the tracking accuracy of single axis PMLSM is affected by uncertainties such as parameter changes and external disturbances.The total uncertainties were estimated and compensated,and the network parameters were adjusted online,so as to resist external disturbances and improve the robustness and tracking performance of the system.Secondly,in order to solve the problem of parameter mismatch and coupling in the operation of dual linear motor,CCC and TSKRFNN were combined.CCC can distribute the single-axis tracking error to two permanent magnet linear synchronous motors(PMLSMs)according to a certain proportion,so as to restrain the unbalanced torque caused by asynchronization and ensure the high-precision synchronous operation of the system.Finally,the validity of the proposed method was verified on the platform of double linear motor.The experimental results show that the proposed method has good robustness and small synchronization error in dynamic process,and can meet the requirements of high precision synchronization control of machining center.