带参数学习的引导信号迭代学习控制方法

针对传统迭代学习控制方法应用在空气舵负载模拟器加载系统中的控制发散问题，提出一种引导信号迭代学习控制方法。为提高和增强新方法的智能型和适应性，并具备更快的收敛速度，对新提出方法进行改进：对引导信号进行迭代学习的同时，也对控制参数进行学习，从而使得新控制方法具备双重学习能力。在系统每个迭代周期初始状态不一致的实际情况下，对新控制方法进行收敛特性的数学分析及证明，并最终给出收敛的充分条件。改进后的控制方法应用在空气舵负载模拟器加载系统仿真模型中进行验证，通过与传统迭代学习控制方法以及不带参数学习的控制方法进行对比，表明带参数学习的引导信号迭代学习控制方法具有更快的收敛速度和更好的控制效果。

Guiding Signal Iterative Learning Control Method with Parameter Learning

An iterative learning control method for guiding signals is proposed to solve the control divergence in using the traditional iterative learning control method in the loading system of air rudder load simulator. The proposed method is improved for improving its intelligence and adaptability and having a faster convergence speed. The control parameters are learned while the iterative learning of the pilot signal is performed, so the proposed control method has dual learning capabilities. Under the actual situation that the initial state of each iteration cycle of the system is inconsistent, the convergence characteristics of the control method are mathematically analyzed and proven, and the sufficient conditions for convergence are finally given. The improved control method is applied to the simulation model of air rudder load simulator loading system for simulation and verification. Compared with the traditional iterative learning control method and the control method without parameter learning, the proposed iterative learning control method with parameter learning has faster convergence speed and better control effect. Key