超声波电机广义最小方差迭代学习转速控制

为减小时变扰动对迭代学习控制性能的影响，将迭代学习控制与广义最小方差自校正控制相结合，给出一种包含预测与闭环控制机制的迭代学习控制策略。通过设计2D目标函数和相应的迭代控制律，利用广义最小方差自校正方法来设计更新律，得到广义最小方差迭代学习控制律，使其同时具有沿迭代轴的学习收敛性和沿时间轴的控制稳定性。仿真和实验表明，所提控制策略有效，控制效果良好，对负载突变等非重复性扰动的适应能力增强。

General Minimum Variance Iterative Learning Speed Control of Ultrasonic Motor

In order to reduce the influence of time-varying disturbance on the performance of iterative learning control, an iterative learning control strategy including prediction and closed-loop control is proposed by combining iterative learning control with self-tuning control of general minimum variance. By designing the two-dimensional (2D) objective function and the corresponding iterative control law, and using the general minimum variance self-tuning method to design the update law, the general minimum variance iterative learning control law is obtained, which can simultaneously guarantee the learning convergence along the cycle index and the control stability along the time index. The results of simulation and experiments indicate that the proposed control strategy is effective, the control performance is good, and the adaptability to non-repetitive disturbances such as sudden load mutation is enhanced.