Adaptive Learning Control for Nonlinear Systems With Randomly Varying Iteration Lengths

This paper proposes adaptive iterative learning control (ILC) schemes for continuous-time parametric nonlinear systems with iteration lengths that randomly vary. As opposed to the existing ILC works that feature nonuniform trial lengths, this paper is applicable to nonlinear systems that do not sati...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transaction on neural networks and learning systems 2019-04, Vol.30 (4), p.1119-1132
Main Authors: Shen, Dong, Xu, Jian-Xin
Format: Article
Language:English
Subjects:
Adaptive control
Adaptive iterative learning control (ILC)
Adaptive learning
Algorithms
composite energy function (CEF)
Computer simulation
Control systems
Convergence
iteration-varying lengths
iterative estimation
Linear systems
Nonlinear control
Nonlinear systems
Parameter estimation
parametric nonlinear systems
Robots
Stochastic processes
Tracking
Tracking errors
Uncertainty
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!