The Analysis of Convergence Speed for an Open and Closed Loop Second Order Iterative Learning Control Algorithm

Author

Xu, Jinxue ; Wang, Dong ; Wang, Xiangdong

Author_Institution

Sch. of Inf. Sci. & Eng., Shenyang Univ. of Technol.

Volume

1

fYear

0

fDate

0-0 0

Firstpage

3905

Lastpage

3909

Abstract

An open-closed-loop second-order iterative learning control algorithm is investigated in the presence of the system uncertainties. Through the rigorous analysis, it is obtained that this algorithm speeds up the convergence rate of iterative learning control in the iteration domain because the closed-loop learning gain is introduced based on an open-loop iterative learning control algorithm. It is proven that this algorithm converges faster than an open-loop iterative learning control algorithm by means of a robust optimization method. Moreover, the convergence rate of the iterative learning control algorithm can be significantly accelerated by the higher closed-loop learning gain. The simulation results for a nonlinear system show the effectiveness of the algorithm

Keywords

adaptive control; closed loop systems; control system analysis; convergence; iterative methods; learning (artificial intelligence); nonlinear control systems; open loop systems; optimisation; closed loop second order iterative learning control; convergence speed; nonlinear system; open loop second order iterative learning control; optimization; Acceleration; Algorithm design and analysis; Control systems; Convergence; Iterative algorithms; Iterative methods; Open loop systems; Optimization methods; Robust control; Uncertainty; convergence speed; iterative learning control; open-closed loop; second-order;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713104

Filename

1713104