Adaptive Iterative Learning Control for Nonlinear Systems With Unknown Control Gain1-Reference-Cited by-同舟云学术

Adaptive Iterative Learning Control for Nonlinear Systems With Unknown Control Gain1

Published:2004-12-01 Issue:4 Volume:126 Page:916-920
ISSN:0022-0434
Container-title:Journal of Dynamic Systems, Measurement, and Control
language:en
Short-container-title:

Author:

Chen Huadong¹,Jiang Ping²

Affiliation:

1. Department of Information and Control Engineering, Tongji University, Shanghai 200092, People’s Republic of China

2. Department of Cybernetics and Virtual Systems, The University of Bradford, Bradford BD7 1DP, UK

Abstract

An adaptive iterative learning control approach is proposed for a class of single-input single-output uncertain nonlinear systems with completely unknown control gain. Unlike the ordinary iterative learning controls that require some preconditions on the learning gain to stabilize the dynamic systems, the adaptive iterative learning control achieves the convergence through a learning gain in a Nussbaum-type function for the unknown control gain estimation. This paper shows that all tracking errors along a desired trajectory in a finite time interval can converge into any given precision through repetitive tracking. Simulations are carried out to show the validity of the proposed control method.

Publisher

ASME International

Subject

Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering

Link

http://asmedigitalcollection.asme.org/dynamicsystems/article-pdf/126/4/916/5502300/916_1.pdf

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