DocumentCode :
2883619
Title :
The benefits of prediction in learning control algorithms
Author :
Owens, David H.
Author_Institution :
Sch. of Eng. & Comput. Sci., Exeter Univ., UK
fYear :
1999
fDate :
1999
Firstpage :
42430
Lastpage :
42432
Abstract :
The emergence of intelligent control has seen a focus of attention on the ideas of learning control. This paper explores the relationship between the performance of learning algorithms and the structure of the system to be controlled. The importance of system´s relative degree (pole-zero excess) and the system´s zeros are described and the role of prediction in improving performance is demonstrated using ideas from iterative learning control
Keywords :
learning systems; convergence; intelligent control; iterative learning control; learning control algorithms; output feedback; pole-zero excess; relative degree; stability; state feedback;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Model Predictive Control: Techniques and Applications - Day 1 (Ref. No. 1999/095), IEE Two-Day Workshop on
Conference_Location :
London
Type :
conf
DOI :
10.1049/ic:19990531
Filename :
771929
Link To Document :
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