Title :
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
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;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1713080
