In this article, the authors study and solve the problem of point-to-point iterative learning control (P2PILC), which only tracks certain key points with unknown batch-varying initial state, thereby eliminating the impact on the output of the initial state error at the final tracking time instants. By completely considering the degree of freedom in point-to-point (P2P) control, an update learning law is designed to compensate the initial state error, and the convergence of the error at the tracking points is proved. At last, the effectiveness of the proposed method is validated by simulation.

中文翻译：

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改进了具有未知批次变化初始状态的批处理的点对点迭代学习控制

在这篇文章中，作者研究并解决了点对点迭代学习控制（P2PILC）的问题，它只跟踪某些初始状态未知的关键点，从而消除了初始状态误差对输出的影响在最后的跟踪时间瞬间。充分考虑点对点（P2P）控制的自由度，设计了一种更新学习律来补偿初始状态误差，证明了误差在跟踪点处的收敛性。最后通过仿真验证了所提方法的有效性。