【摘要】 数控机床的主轴驱动系统决定了机床的动态特性、加工精度等关键技术指标,其核心部件永磁同步电机的控制精度及稳定性必须进行优化。在传统PI反馈控制的基础上提出一种基于在线智能前馈补偿自学习的优化控制方法。该在线智能前馈补偿控制使用简单迭代学习规则,以补偿重复负载转矩和模型参数的不确定性,无需对系统模型进行辨识。推导证明了此优化策略可满足系统响应的稳定性和收敛性要求。实验结果也证明了该优化策略的有效性和可行性,可为数控机床的主轴驱动系统优化设计提供参考。更多还原

【Abstract】 Spindle drive system determines key technical indexes such as dynamic characteristics,machining accuracy etc in NC machine. As the key part,permanent magnet synchronous motor should be optimalized for the control accuracy and stability. An optimal control strategy was proposed based on online feedforward self-learning combined with the traditional PI feedback control. In the feed forward compensator,a simple learning rule was used for the load torque disturbance and model uncertainty,the information of the motor parameters and load torque values were not required. It is proved the optimal control strategy can meet the demand on system stability and convergence through derivation. Experimental results verify the effectiveness of the proposed method,which can provide reference for optimal design of NC machine.更多还原