Title :
Iterative learning control-convergence using high gain feedback
Author_Institution :
Centre for Syst. & Control Eng., Exeter Univ., UK
Abstract :
The author presents a convergence theory for iterative learning control based on the use of high-gain current trial feedback for the special case of relative degree one, MIMO (multiple-input multiple-output) minimum-phase systems. The results are related to those of Padieu and Su (1990) via the notion of positive real systems. In particular, positive real systems are easily arranged to have convergent learning by simple proportional learning rules of arbitrary positive gain
Keywords :
convergence; feedback; iterative methods; learning systems; MIMO; convergence theory; convergent learning; high gain feedback; iterative learning control; minimum-phase systems; positive real systems; Control engineering; Control systems; Convergence; Error correction; Feedback; Iterative algorithms; MIMO; Robots; Signal generators; Stability; Topology;
Conference_Titel :
Decision and Control, 1992., Proceedings of the 31st IEEE Conference on
Conference_Location :
Tucson, AZ
Print_ISBN :
0-7803-0872-7
DOI :
10.1109/CDC.1992.371067
