基于神经网络的迭代控制器在超声马达速度控制中的应用

A Neural-Network-Based Iterative Controller for Speed Control of Ultrasonic Motors

针对超声马达的速度控制问题提出了一种基于神经网络方法的迭代控制器。通过理论分析给出了保证控制器最快收敛的自适应学习率。数值结果表明该控制器对于多种形式的参考速度都有较好的控制效果 ,其控制精度与已有方法相比有较大提高。模拟结果还表明该方法对于随机扰动有较强的鲁棒性。

A neural-network-based iterative controller is presented for the speed control of ultrasonic motors. Suitable ranges of the adaptive learning rates are presented through the theoretical analysis on the proposed model, which could guarantee the fastest convergence of the neural network controller. Numerical results show that the neural-network-based controller is effective for various kinds of reference speeds of ultrasonic motors. Comparisons with the existing method show that the precision of control is increased using the proposed method. Simulations also show that the proposed scheme is fairly robust against random disturbance to the control variables.