摘要
This paper proposes a self-tuning iterative learning control method for the attitude control of a flexible solar power satellite,which is simplified as an Euler-Bernoulli beam moving in space.An orbit-attitude-structure coupled dynamic model is established using absolute nodal coordinate formulation,and the attitude control is performed using two control moment gyros.In order to improve control accuracy of the classic proportional-derivative control method,a switched iterative learning control method is presented using the control moments of the previous periods as feedforward control moments.Although the iterative learning control is a model-free method,the parameters of the controller must be selected manually.This would be undesirable for complicated systems with multiple control parameters.Thus,a self-tuning method is proposed using fuzzy logic.The control frequency of the controller is adjusted according to the averaged control error in one control period.Simulation results show that the proposed controller increases the control accuracy greatly and reduces the influence of measurement noise.Moreover,the control frequency is automatically adjusted to a suitable value.
提出了柔性空间太阳能电站姿态控制的自调节迭代学习控制方法。将空间太阳能电站简化为在轨运行的欧拉-伯努利梁,采用绝对节点坐标法建立了轨道-姿态-结构耦合动力学模型。采用2个控制力矩陀螺实现姿态控制。为了提高经典比例-微分控制方法的控制精度,提出了切换迭代学习控制方法,采用以往周期控制力矩作为当前周期的前馈控制力矩。尽管迭代学习控制方法是一种无模型控制方法,其控制参数必须手动选择,给多可调参数的复杂控制系统设计带来困难。因此,采用模糊逻辑提出了一种自调节方法,可根据一个控制周期内平均控制误差自动调节控制器的控制频率。仿真结果表明,本文提出的控制方法可极大地提高控制精度,减小传感器噪声的影响,而且控制频率可自动调整至合适的值。
基金
supported by the Guangdong Basic and Applied Basic Research Foundation(No.2019A1515110730)
the Young Elite Scientists Sponsorship Program by China Association for Science and Technology(No.2021QNRC001)
the Fundamental Research Funds for the Central Universities of Sun Yat-sen University(No.22qntd0703)。
