二维直线电机的并联型无模型自适应复合控制

Parallel Model-free Adaptive Composite Control for Two-axis Linear Motor

针对二维直线电机平台系统的XY轴协同控制问题,将PI与并联型无模型自适应相结合的复合控制方法应用于控制系统。该控制方法通过在每个子系统加入PI控制方法保证其稳定性,再通过并联型的无模型自适应控制方法来提高整个系统的跟踪性能,以减小系统位置误差。基于数据驱动的无模型自适应控制方法设计二维直线电机系统控制器,其优势在于无需被控系统精确数学模型,仅根据被控系统输入输出数据对系统进行控制。相比基于模型的控制方法,该方法能够减小未建模动态产生的干扰,有效提高控制精度。仿真及实物控制效果对比结果表明,这种复合控制方法明显提高了整个系统的稳定性和位置跟踪精度。

Considering the XY-axis cooperative problem in the two-axis linear motor platform system, the composite control method that combines PI with parallel model-free adaptive control is applied to the control system. This method can reduce position error of the system by adding PI control method into its subsystem to ensure stability as well as parallel model-free adaptive control method to improve its tracking performance. Based on the data-driven model-free adaptive control method, the controller of two-axis linear motor system is designed. Its advantage is that it does not need the precise mathematical model of the controlled system, and only controls the system according to the input and output data of the controlled system. Compared with the model-based control method, this method can reduce the disturbance caused by unmodeled dynamics and effectively improve the control accuracy. The comparison of simulation and physical control results shows that the composite control method can improve the stability and position tracking accuracy of the whole system obviously.