Open AccessFractional-order iterative learning control for robotic Arm-PD2Dα type
Author(s) -
P. Cvetković,
Predrag Lazarević
Publication year - 2021
Publication title -
filomat
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.449
H-Index - 34
eISSN - 2406-0933
pISSN - 0354-5180
DOI - 10.2298/fil2101001c
Subject(s) - iterative learning control , robustness (evolution) , mathematics , control theory (sociology) , convergence (economics) , tracking error , trajectory , robotic arm , gronwall's inequality , computer science , artificial intelligence , control (management) , inequality , mathematical analysis , biochemistry , chemistry , physics , astronomy , economics , gene , economic growth
In this paper, a new open-loop PD2D? type a fractional order iterative learning control (ILC) is studied for joint space trajectory tracking control of a linearized uncertain robotic arm. The robust convergent analysis of the tracking errors has been done in time domain where it is theoretically proven that the boundednesses of the tracking error are guaranteed in the presence of model uncertainty. The convergence of the proposed open-loop ILC law is proven mathematically using Gronwall integral inequality for a linearized robotic system and sufficient conditions for convergence and robustness are obtained.