DocumentCode :
2339393
Title :
Analysis of continuous iterative learning control systems using current cycle feedback
Author :
Xu, Jian-Xin ; Wang, Xiao-Wei ; Heng, Lee Tong
Author_Institution :
Dept. of Electr. Eng., Nat. Univ. of Singapore, Singapore
Volume :
6
fYear :
1995
fDate :
21-23 Jun 1995
Firstpage :
4221
Abstract :
In this paper, a continuous iterative-learning control scheme with current cycle feedback (CCF type) is studied. Through theoretical analysis and comparison, we prove that faster convergence rate of the CCF type learning control can be achieved by selecting a higher feedback gain. In addition, owing to the current cycle error feedback, the control system is robust against any unpredictable small perturbation. In this paper, the multiperiod learning strategy is further developed in conjunction with the current cycle feedback algorithm. The method extended to the MIMO case. Finally, a number of case studies are carried out which support the aforementioned statements
Keywords :
MIMO systems; control system analysis; feedback; iterative methods; learning systems; multivariable control systems; MIMO systems; continuous iterative learning control systems analysis; convergence rate; current cycle error feedback; feedback gain; multiperiod learning strategy; Artificial intelligence; Control systems; Convergence; Error correction; Nonlinear dynamical systems; Nonlinear equations; Nonlinear systems; Output feedback; Performance analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, Proceedings of the 1995
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-2445-5
Type :
conf
DOI :
10.1109/ACC.1995.532728
Filename :
532728
Link To Document :
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