An algorithm of adaptive iterative learning control based on process models

Author

Zhai, Chunyan ; Xue, Dingyu ; Li, Shuchen

Author_Institution

Sch. of Inf. & Control Eng., Liaoning Shihua Univ., Fushun, China

fYear

2010

fDate

26-28 May 2010

Firstpage

3009

Lastpage

3012

Abstract

An algorithm of adaptive iterative learning control (AILC) based on model is proposed for a class of CARMA models with repetitive trajectory in a specific period of time. Process model parameters are identificated using previous time data and AILC law of the current time is constituted by process model parameters. Convergence and stability are analyzed. The algorithm for linear stable process can achieve the unbiased fast-tracking. Several simulation examples demonstrate the effectiveness and robustness of the algorithm.

Keywords

adaptive control; convergence; iterative methods; learning systems; stability; CARMA models; adaptive iterative learning control; convergence; process model parameter; repetitive trajectory; stability; unbiased fast-tracking; Adaptive control; Control engineering; Convergence; Electronic mail; Information science; Iterative algorithms; Process control; Programmable control; Stability analysis; Three-term control; CARMA model; adaptive; iterative learning control; system identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2010 Chinese

Conference_Location

Xuzhou

Print_ISBN

978-1-4244-5181-4

Electronic_ISBN

978-1-4244-5182-1

Type

conf

DOI

10.1109/CCDC.2010.5498655

Filename

5498655