潘颖,薄翠梅,何文敏,李俊

• 1:南京工业大学电气工程与控制科学学院
• 2:南京工业大学智能制造研究院

摘要(Abstract)：

针对一类包含不确定性和非重复性的间歇过程鲁棒性问题，设计了一种基于扩张状态观测器(ESO)的比例-微分(PD）型迭代学习控制(ILC)策略。通过ESO估计系统受到的总扰动，结合PD型间接迭代学习控制律对自抗扰控制器进行批次轴上的迭代更新，实现批次轴和时间轴两个方向上的控制律修正优化。此外，对间歇反应釜和橡胶密炼过程的仿真结果表明，所提出的基于扩张观测器的自抗扰迭代学习策略能有效抑制外部不确定干扰，改善系统的鲁棒性与控制精度。

关键词(KeyWords)： 间歇过程;迭代学习控制;PD型迭代学习;自抗扰控制;扩张状态观测器

Abstract:

Keywords:

基金项目(Foundation): 国家重点研发计划(2022YFB3305300);; 国家自然科学基金(62333010,62173178)

作者(Author): 潘颖,薄翠梅,何文敏,李俊

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