Analyze initial state errors of point-to-point iterative learning control for batch process

HONG Yingdong; XIONG Zhihua; JIANG Yongheng; YE Hao

doi:10.11949/j.issn.0438-1157.20170106

您当前的位置：

首页 >

文章列表页 >

Analyze initial state errors of point-to-point iterative learning control for batch process

更新时间：2025-12-10

- Analyze initial state errors of point-to-point iterative learning control for batch process
- CIESC Journal Issue 7, Pages: 2826-2832(2017)
- 作者机构：
  
  清华大学自动化系,北京,100084
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20170106
  CLC： P13
- Online First：05 July 2017，
  
  Published：05 July 2017
- 稿件说明：
移动端阅览
HONG Yingdong, XIONG Zhihua, JIANG Yongheng, et al. Analyze initial state errors of point-to-point iterative learning control for batch process[J]. CIESC Journal, 2017, (7): 2826-2832.
DOI：

HONG Yingdong, XIONG Zhihua, JIANG Yongheng, et al. Analyze initial state errors of point-to-point iterative learning control for batch process[J]. CIESC Journal, 2017, (7): 2826-2832. DOI： 10.11949/j.issn.0438-1157.20170106.

摘要

针对间歇过程点对点跟踪控制问题，在轨迹更新的迭代学习控制算法框架下，针对非理想初始状态情况下3种不同的初始误差，通过2D Roesser模型对其进行描述并分析其收敛性。给出了不同的情况下系统相对参考轨迹的零误差跟踪或者收敛到特定邻域的条件，在零误差跟踪不能实现的情况下给出了邻域的范围。通过数值模型仿真验证了给出的收敛条件和收敛边界，并分析了不同因素对收敛边界的影响。

Abstract

To address problems of point-to-point tracking control for batch processes

three different initial errors of non-ideal initial states were analyzed and studied for convergence by 2 D Roesser model within the framework of tracking control algorithm. Conditions were provided to achieve zero or a neighborhood of zero tracking control errors between system and reference trajectory at various scenarios. For these unable to achieve zero tracking errors

boundaries of final tracking errors were given. Numerical simulation validated these convergence conditions and boundaries

and assessed effect of control parameters on these boundaries.

关键词

Keywords

references

Views

203

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

2D-PID adaptive control method for time-varying batch processes

Iterative learning control of batch process with input trajectory parameterization

Study on microstructure of NaCl solution ice centrifugal separation based on Micro-CT and deep learning

Research on the characterization of the molecular weight and its distribution of perfluoropolyether

Analysis of flow field characteristics and mixing performance of different SK-type static mixers

Related Author

WANG Zhiwen

LIU Yi

GAO Zengliang

YE Lingjian

MA Xiushui

SONG Zhihuan

Related Institution

Engineering Research Center of Equipment and Remanufacturing (Ministry of Education), Zhejiang University of Technology

Ningbo Institute of Technology, Zhejiang University

Department of Control Science and Engineering, Zhejiang University

⁰