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ADAPTIVE ITERATIVE LEARNING CONTROL OF ROBOTIC SYSTEMS USING BACKSTEPPING DESIGN

Ying‐Chung Wang, Chiang‐Ju Chien, Chi-Nan Chuang

Year
2013
Citations
6

Abstract

In this paper, a backstepping adaptive iterative learning control (AILC) is proposed for robotic systems with repetitive tasks. The AILC is designed to approximate unknown certainty equivalent controller. Finally, we apply a Lyapunov like analysis to show that all adjustable parameters and the internal signals remain bounded for all iterations.

Keywords

BacksteppingIterative learning controlControl theory (sociology)Bounded functionAdaptive controlController (irrigation)Computer scienceLyapunov functionControl engineeringControl (management)

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