An Open-Closed-Loop Gradient-Type ILC Combined with Infinite Time Optimal Output LQR

Author

Liu, Shan ; Chen, Hong

Author_Institution

National Lab. of Ind. Control Technol., Zhejiang Univ., Hangzhou

Volume

1

fYear

0

fDate

0-0 0

Firstpage

3791

Lastpage

3795

Abstract

Based on the iterative learning control (ILC) architecture combining feedforward term and feedback term, a sufficient convergence condition of the closed system is obtained for linear system while the gradient method is used to design the feedforward action. In order to improve the convergence rate of learning in iterations, a simple iterative learning law employing the infinite time optimal output LQR is proposed for LTI plant and its convergence and robustness are analyzed in detail. The effectiveness of the above ILC law is demonstrated by the simulation studies

Keywords

closed loop systems; control system analysis; feedback; feedforward; gradient methods; learning systems; linear systems; open loop systems; feedback term; feedforward term; gradient method; infinite time optimal output LQR; iterative learning control; learning convergence rate; linear system; open-closed-loop gradient-type ILC; sufficient convergence condition; Control systems; Convergence; Electronic mail; Gradient methods; Industrial control; Iterative methods; Laboratories; Linear feedback control systems; Linear systems; Robustness; convergence rate of learning; gradient method; infinite time optimal output LQR; iterative learning control;

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.2006.1713080

Filename

1713080