永磁直线电机的无模型学习自适应控制

Model-free Learning Adaptive Control of Permanent Magnet Linear Motor

将单入单出非线性离散时间系统的非参数模型学习自适应控制方法应用在永磁直线电机的速度和位置控制中。设计是无模型的,是直接基于称为伪偏导数的向量,此伪偏导数是通过一种新型参数估计算法,根据系统的输入输出信息在线导出的。仿真实验证明了该方法对具有不确知动态的非线性系统的有效性和稳定性。

In this paper, the model-free learning adaptive control（MFLAC） approach of a class of SISO non- linear discrete-time systems is applied to permanent magnet linear motor speed and position control. The design is model-free, based directly on pseudo-partial-derivatives（PPD） derived on-line from the input and output information of the system using a novel parameter estimation algorithm. Validity and stability are proved for nonlinear systems with vaguely known dynamics by the simulation examples.