Open AccessRobust ILC of Nonlinearly Parametric Time-Delay Systems with Input Deadzone
Author(s) -
Xidan Wang,
Yuhan Ma,
Qingdong Yan,
Yuntao Zhang,
Xiaohui Guan
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2025/1/012079
Subject(s) - iterative learning control , control theory (sociology) , dead zone , parametric statistics , trajectory , computer science , adaptive control , position (finance) , interval (graph theory) , tracking (education) , mathematics , control (management) , artificial intelligence , physics , pedagogy , oceanography , statistics , economics , geology , finance , combinatorics , astronomy , psychology
The trajectory tracking problem for a class of nonlinearly parametric systems with input deadzone and time-delay is studied in this work. An adaptive iterative learning control (ILC) scheme is developed by using Lyapunov synthesis. The alignment condition is applied to solve the initial position problem of ILC. Robust control and ILC are used to deal with input deadzone, delay and nonlinearly parametric uncertainties, together. As the iteration learning cycle increases, the system state may precisely track the reference signal over the whole interval. A numerical simulation is presented to verify the efficacy of the proposed adaptive iterative learning control method.