A unified adaptive control approach of nonlinear continuous non‐parameterized systems with asymmetric control gains for trajectory tracking in different domains

In this article, for nonlinear continuous non‐parameterized (NCNP) systems, an adaptive iterative learning control (ILC) algorithm, which can adjust the adaptive parameters in both iteration‐domain and time‐domain, is first proposed to track different reference trajectories repetitively over a finit...

Full description

Saved in:
Bibliographic Details
Published in:International journal of robust and nonlinear control 2023-05, Vol.33 (7), p.3964-3987
Main Authors: Ding, Ya‐Qiong, Li, Xiao‐Dong
Format: Article
Language:English
Subjects:
Adaptive control
adaptive iterative learning control
Adaptive systems
Algorithms
asymmetric control gain
Asymptotic properties
Controllers
Domains
Iterative methods
Machine learning
nonlinear continuous non‐parameterized systems
Nonlinear control
Nussbaum gain
Parameterization
reference trajectory tracking
Tracking control
Trajectory control
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this article, for nonlinear continuous non‐parameterized (NCNP) systems, an adaptive iterative learning control (ILC) algorithm, which can adjust the adaptive parameters in both iteration‐domain and time‐domain, is first proposed to track different reference trajectories repetitively over a finite time interval. As the NCNP system is required to asymptotically track reference trajectory in infinite time‐domain, by virtue of partitioning the reference trajectory and system signals with a fixed time interval, the proposed adaptive ILC controller is then extended to handle the asymptotic tracking issue in infinite time‐domain. Therefore, a unified adaptive control approach is practically presented for NCNP systems to track reference trajectories in different domains (the infinite iteration‐domain and the infinite time‐domain). A prominent feature of the unified adaptive control approach is that the unknown control gain matrices in the NCNP systems are assumed to be invertible only. As a result, the general requirement in conventional adaptive control and adaptive ILC that the control gain matrices of plants are real symmetric and positive‐definite (or negative‐definite) is greatly relaxed. In addition, only three adaptive variables are designed for adjusting or updating in the proposed unified adaptive control approach such that the structure of controller is very simple and the memory space for computing is saved.
ISSN:1049-8923
1099-1239
DOI:10.1002/rnc.6305