永磁直线电机的无模型自适应控制方法研究

Study of model-free adaptive control method in permanent magnet linear motor

将基于全格式线性化的单入单出非线性离散时间系统的无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。控制器的设计是无模型的,是直接基于称为拟梯度的向量,拟梯度向量是通过新型参数估计算法,根据给出的永磁直流直线电机运动模型的输入输出信息在线导出的。无模型控制方法非常适用于实际的阶数难以知道或难以辨识,且是时变的非线性系统。实现了系统阶数较高时的有效控制,弥补了经典自适应控制阶数高时在线计算量过大而不能适应于系统快速变化过程的不足。利用Matlab软件进行仿真实验,验证了该方法对电机这种具有不确知动态的非线性系统的稳定性和抑止外部干扰和噪声的有效性和鲁棒性。

The model-free learning adaptive control （MFLAC） approach of a class of SISO nonlinear discrete-time systems based on linearization of entire format is applied to permanent magnet linear motor speed and position control. The design of controller is modelfree, based directly on gradient-like vector derived on-line from the input and output information of the motor motion model using novel parameter estimation algorithms. The model-free control is especially useful for real nonlinear systems whose orders and modeling are very difficult to be known and time varying. The control is very effective when model orders are too high that the classical adaptive control needs too much computering resource to deal with its heavy computation burden in order to meeting the requirement of the rapid system response. Stability, validity and robustness against exogenous disturbance and noise are demonstrated by simulations using Matlab for the nonlinear systems of motor with vaguely known dynamics.