带有参数精确估计的迭代学习滑模控制及应用
收稿日期: 2023-04-19
修回日期: 2023-06-05
录用日期: 2023-07-17
网络出版日期: 2023-07-21
基金资助
国家自然科学基金(62073096);黑龙江省头雁行动计划
Iterative learning sliding mode control with precise parameter estimation and its application
Received date: 2023-04-19
Revised date: 2023-06-05
Accepted date: 2023-07-17
Online published: 2023-07-21
Supported by
National Natural Science Foundation of China(62073096);Heilongjiang Touyan Innovation Team Program
针对一类做重复运动的不确定全驱系统，提出了一种带有未知参数精确估计的迭代学习自适应滑模控制算法。通过设计跟踪误差的期望轨迹，放宽了对系统初值条件的限制，并使系统在初始时刻便位于滑模面上，消除了滑模到达阶段，有利于提高系统鲁棒性。通过构造一组低通滤波器并引入遗忘因子和归一化技术，对参数估计误差进行了重构，并利用重构结果进行了微分-差分型自适应律设计。基于Lyapunov方法设计了迭代学习自适应滑模控制算法，证明了闭环系统信号的有界性以及跟踪误差和参数估计误差的渐近收敛性。最后，将所提出的迭代学习自适应滑模控制算法应用于航天器的绕飞控制中，并通过数值仿真验证了设计结果的有效性。
方乐言 , 蒙晗 , 侯明哲 . 带有参数精确估计的迭代学习滑模控制及应用[J]. 航空学报, 2024 , 45(1) : 628889 -628889 . DOI: 10.7527/S1000-6893.2023.28889
An iterative learning adaptive sliding mode control algorithm with precise estimation of unknown parameters is proposed for a class of uncertain fully actuated systems with repetitive motions. By designing a desired trajectory of the tracking error， the strict requirement on the system initial condition is relaxed and the system is ensured to be on the sliding mode surface at the initial moment， which eliminates the reaching phase of the sliding mode and is beneficial for improving the robustness of the system. By constructing a set of low-pass filters and introducing forgetting factors and the normalization technique， the parameter estimation errors are reconstructed， and then the reconstruction results are utilized to design the differential-difference adaptive laws. Based on the Lyapunov theory， an iterative learning adaptive sliding mode control algorithm is designed， and it is proved that all signals of the closed-loop system are bounded， and the tracking errors and the parameter estimation errors asymptotically converge to zero. Finally， the proposed iterative learning adaptive sliding mode control algorithm is applied to the fly-around control of spacecraft， and the effectiveness of the obtained results is verified via numerical simulations.
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