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research-article

A Unified Design Approach to Repetitive Learning Control for Systems Subject to Fractional Uncertainties

[+] Author and Article Information
Mingxuan Sun

Professor, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
mxsun@zjut.edu.cn

He Li

Graduate Student, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
hlihz@hotmail.com

Yanwei Li

Graduate Student, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
lyw199202@163.com

1Corresponding author.

ASME doi:10.1115/1.4038488 History: Received February 25, 2017; Revised November 06, 2017

Abstract

Fractional uncertainties are involved in many practical systems. Currently, there are lack of research results about such general class of nonlinear systems, in the context of learning control. This paper presents a Lyapunov-synthesis approach to repetitive learning control, being unified due to the use of the direct parametrization and adaptive bounding techniques. To effectively handle fractional uncertainties, the estimation method for such uncertainties is elaborated to facilitate the controller design and convergence analysis. Its novelty lies in the less requirement for the knowledge about the system undertaken. Unsaturated- and saturated-learning algorithms are respectively characterized, by which both the boundedness of the variables in the closed-loop system undertaken and the asymptotical convergence of the tracking error are established. Experimental results are provided to verify the effectiveness of the presented learning control.

Copyright (c) 2017 by ASME
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