高校化学工程学报2026，Vol.40Issue(2)：262-270,9.DOI:10.3969/j.issn.1003-9015.2025.00.014
基于扩张观测器的间歇过程迭代学习自抗扰控制
Iterative learning active disturbance rejection control based on extended state observer for batch process
摘要
Abstract
To address the robustness issues in a class of batch processes characterized by uncertainty and non-repeatability,a proportional-derivative(PD)type iterative learning control(ILC)strategy based on an extended state observer(ESO)was designed.The ESO was employed to estimate the total disturbances acting on the system,and an indirect PD-type ILC law was applied to iteratively update the disturbance-rejection controller along the batch axis.This enabled joint optimization of the control law in both the time and batch domains.Simulation results on a batch reactor and a rubber internal mixing process demonstrated that the proposed ESO-based iterative disturbance-rejection learning strategy effectively suppressed external uncertain disturbances and improved the system's robustness and control accuracy.关键词
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Key words
batch processes/iterative learning control/PD-type iterative learning/active disturbance reject control/extended state observer分类
信息技术与安全科学引用本文复制引用
潘颖,薄翠梅,何文敏,李俊..基于扩张观测器的间歇过程迭代学习自抗扰控制[J].高校化学工程学报,2026,40(2):262-270,9.基金项目
国家重点研发计划(2022YFB3305300) （2022YFB3305300）
国家自然科学基金(62333010,62173178). （62333010,62173178）
