基于迭代学习的电动负载模拟器复合控制

为保证电动负载模拟器力矩精确加载,设计了基于迭代学习控制和舵机位置前馈补偿结合的复合力矩控制器.引入弹性杆结构以提高系统稳定性及加载精度,并从系统响应速度、频宽及稳定性等方面对弹性杆刚度约束进行了分析.建立了控制系统模型,在三闭环结构基础上,引入了舵机位置前馈补偿.为保证正弦负载模拟效果,设计了基于指令力矩幅值和相位修正的迭代学习控制器,并基于P型控制器实现对幅值和相位的迭代学习.最后,分别进行了力矩加载及多余力矩抑制实验,结果证明了该方法的可行性及有效性.

Composite control for electric load simulator based on iterative learning

A composite torque controller combining iterative learning control and the feedforward compensation of a rudder angle was built for an electric load simulator in order to increase loading accuracy. The spring beam was used to improve the system stability and the loading accuracy, and constraints to the stiffness coefficient of the spring beam were analyzed based on system response speed, frequency width and stability. The mathematical models of plants were established, and three close loops were used. The feedforward compensation of the rudder angular displacement was introduced into the torque controller. The iterative learning controller was designed by modifying the magnitude and the phase of the command torque to improve loading effects, and P-type iterative learning controller was used. Finally, experiments of loading torque and testing the extraneous torque were performed, and experiment results proved that this controller is effective in achieving a perfect torque tracking accuracy and restraining the extraneous torque for electric load simulators.