Iterative learning control of batch process with input trajectory parameterization

YE Lingjian; MA Xiushui; SONG Zhihuan

doi:10.11949/j.issn.0438-1157.20151929

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Iterative learning control of batch process with input trajectory parameterization

更新时间：2025-12-10

- Iterative learning control of batch process with input trajectory parameterization
- CIESC Journal Issue 3, Pages: 743-750(2016)
- 作者机构：
  
  1. 浙江大学宁波理工学院,浙江,宁波,315100
  2. 浙江大学控制科学与工程学系,浙江,杭州,310027
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20151929
  CLC： P273
- Online First：12 January 2016，
  
  Published：12 January 2016
- 稿件说明：
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YE Lingjian, MA Xiushui, SONG Zhihuan. Iterative learning control of batch process with input trajectory parameterization[J]. CIESC Journal, 2016, (3): 743-750.
DOI：

YE Lingjian, MA Xiushui, SONG Zhihuan. Iterative learning control of batch process with input trajectory parameterization[J]. CIESC Journal, 2016, (3): 743-750. DOI： 10.11949/j.issn.0438-1157.20151929.

摘要

针对间歇过程的迭代学习控制问题

提出了一种基于输入轨迹参数化的迭代学习控制策略。根据最优输入轨迹的主要形态特征

将其参数化为较少量的决策变量

降低传统迭代学习控制复杂性的同时维持良好的优化控制效果。基于输入轨迹参数化的迭代学习控制策略能保持算法的简洁性和易实现性

在不确定扰动影响下逐步改善产品质量。对一个间歇反应器的仿真研究验证了本文方法的有效性。

Abstract

An iterative learning control (ILC) approach with input trajectory parameterization is proposed for batch processes. In the new approach

the main characteristics of the optimal input profile are obtained to parameterize the whole input trajectory with a few scholar decision variables. The proposed ILC method maintains the simplicity of the algorithm

while improving the optimizing control performance from batch to batch under uncertainties. A batch reactor is simulated to demonstrate the effectiveness of proposed ILC method.

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