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An iterative learning control theory for a class of nonlinear dynamic systems

โœ Scribed by Tae-Yong Kuc; Jin S. Lee; Kwanghee Nam

Publisher
Elsevier Science
Year
1992
Tongue
English
Weight
568 KB
Volume
28
Category
Article
ISSN
0005-1098

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โœฆ Synopsis

An iterative learning control scheme is presented for a class of nonlinear dynamic systems which includes holonomic systems as its subset. The control scheme is composed of two types of control methodology: a linear feedback mechanism and a feedforward learning strategy. At each iteration, the linear feedback provides stability of the system and keeps its state errors within uniform bounds. The iterative learning rule, on the other hand, tracks the entire span of a reference input over a sequence of iterations. The proposed learning control scheme takes into account the dominant system dynamics in its update algorithm in the form of scaled feedback errors. In contrast to many other learning control techniques, the proposed learning algorithm neither uses derivative terms of feedback errors nor assumes external input perturbations as a prerequisite. The convergence proof of the proposed learning scheme is given under minor conditions on the system parameters. *

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