Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System

Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System

This paper proposes an adaptive iterative learning control strategy integrated with saturation-based robust control for uncertain robot system in presence of modelling uncertainties, unknown parameter, and external disturbance under alignment condition. An important merit is that it achieves adaptiv...

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Main Authors: Guofeng Tong, Mingxiu Lin
Format: Article
Language:English
Published: SAGE Publishing 2014-04-01
Series:Advances in Mechanical Engineering
Online Access:https://doi.org/10.1155/2014/201317
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spelling doaj-4774df5080b841b58aa2dd93a0deb47f2020-11-25T03:44:31ZengSAGE PublishingAdvances in Mechanical Engineering1687-81322014-04-01610.1155/2014/20131710.1155_2014/201317Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot SystemGuofeng TongMingxiu LinThis paper proposes an adaptive iterative learning control strategy integrated with saturation-based robust control for uncertain robot system in presence of modelling uncertainties, unknown parameter, and external disturbance under alignment condition. An important merit is that it achieves adaptive switching of gain matrix both in conventional PD-type feedforward control and robust adaptive control in the iteration domain simultaneously. The analysis of convergence of proposed control law is based on Lyapunov's direct method under alignment initial condition. Simulation results demonstrate the faster learning rate and better robust performance with proposed algorithm by comparing with other existing robust controllers. The actual experiment on three-DOF robot manipulator shows its better practical effectiveness.https://doi.org/10.1155/2014/201317
collection DOAJ
language English
format Article
sources DOAJ
author Guofeng Tong
Mingxiu Lin
spellingShingle Guofeng Tong
Mingxiu Lin
Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System
Advances in Mechanical Engineering
author_facet Guofeng Tong
Mingxiu Lin
author_sort Guofeng Tong
title Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System
title_short Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System
title_full Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System
title_fullStr Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System
title_full_unstemmed Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System
title_sort alignment condition-based robust adaptive iterative learning control of uncertain robot system
publisher SAGE Publishing
series Advances in Mechanical Engineering
issn 1687-8132
publishDate 2014-04-01
description This paper proposes an adaptive iterative learning control strategy integrated with saturation-based robust control for uncertain robot system in presence of modelling uncertainties, unknown parameter, and external disturbance under alignment condition. An important merit is that it achieves adaptive switching of gain matrix both in conventional PD-type feedforward control and robust adaptive control in the iteration domain simultaneously. The analysis of convergence of proposed control law is based on Lyapunov's direct method under alignment initial condition. Simulation results demonstrate the faster learning rate and better robust performance with proposed algorithm by comparing with other existing robust controllers. The actual experiment on three-DOF robot manipulator shows its better practical effectiveness.
url https://doi.org/10.1155/2014/201317
work_keys_str_mv AT guofengtong alignmentconditionbasedrobustadaptiveiterativelearningcontrolofuncertainrobotsystem
AT mingxiulin alignmentconditionbasedrobustadaptiveiterativelearningcontrolofuncertainrobotsystem
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