Journal of South China University of Technology (Natural Science Edition) ›› 2020, Vol. 48 ›› Issue (1): 114-122.doi: 10.12141/j.issn.1000-565X.190195

• Electronics, Communication & Automation Technology • Previous Articles     Next Articles

Iterative Learning Control for Linear Differential Repetitive Processes with Regional Pole Constraints#br#

WANG Lei1 YANG Huizhong1 TAO Hongfeng1 Wojciech Paszke2   

  1. 1． Key laboratory of Advanced Process Control for Light Industry of Ministry of Education，Jiangnan University，Wuxi 214122，Jiangsu，China; 2． Institute of Control and Computation Engineering，University of Zielona Gora，ul． Szafrana 2，65-516 Zielona Gora，Poland
  • Received:2019-04-19 Revised:2019-06-20 Online:2020-01-25 Published:2019-12-01
  • Contact: 汪磊(1989-)，男，博士生，主要从事迭代学习控制研究。 E-mail:leiwang112@126.com
  • About author:汪磊(1989-)，男，博士生，主要从事迭代学习控制研究。
  • Supported by:
    Supported by the National Natural Science Foundation of China (61773181) and the National Science Centre in Poland (2017/27/B/ST7/01874)

RichHTML

3

PDF

164

Abstract: Existing studies on iterative learning control focus on the robust convergence of the iterative learning control system along the trial direction，and pay little attention to the performance along the time direction，which fails to show the dynamic characteristics of the control system． Iterative learning control for linear differential repet-itive processes with regional pole constraints was studied． Firstly，combining with the two-dimensional (2D) sys-tem theory，the 2D continuous Roesser model was built under the time domain． Then，based on the Kalman-Yakubovich-Popov lemma，the tracking performance of iterative learning control systems and regional pole con-straints problems were analyzed． Moreover，the sufficient conditions of existence for the controller were derived in terms of linear matrix inequalities，which can guarantee the system performance along the trial direction and the time direction． Furthermore，the results are extended to structural uncertainty model as well． Finally，the simula-tions for a typical actuator of tracking servo system prove that the design is effective and feasible．

Key words: linear differential repetitive process, regional pole constraint, iterative learning control, Kalman-Yakubovich-Popov lemma

CLC Number: