A new neural network-based adaptive ILC for nonlinear discrete-time systems with dead zone scheme
type: Item
instance of: scholarly article
title: A new neural network-based adaptive ILC for nonlinear discrete-time systems with dead zone scheme
zbMATH Open document ID: 1193.93130
author: Ronghu Chi
author: Zhongsheng Hou
published in: Journal of Systems Science and Complexity
publication date: 2010-05-03T00:00:00Z
Mathematics Subject Classification ID: 93C55
Mathematics Subject Classification ID: 93C10
Mathematics Subject Classification ID: 93C40
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 92B20
zbMATH DE Number: 5703311
zbMATH Keywords: adaptive control
zbMATH Keywords: iterative learning control
zbMATH Keywords: neural network
zbMATH Keywords: non-identical initial condition
zbMATH Keywords: non-identical trajectory
MaRDI profile type: Publication
full work available at URL: s11424-009-9176-4
OpenAlex ID: W2031783946
cites work: Adaptive regulation of nonlinear systems with unmodeled dynamics
cites work: Adaptive control of linearizable systems
cites work: Adaptive output-feedback control of systems with output nonlinearities
cites work: Adaptive control of nonlinear systems using neural networks
cites work: Adaptive control of a class of nonlinear discrete-time systems using neural networks
cites work: Iterative learning control. Convergence, robustness and applications
cites work: Analysis of iterative learning control for a class of nonlinear discrete-time systems
cites work: Multilayer feedforward networks are universal approximators
DOI: 10.1007/S11424-009-9176-4
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description: scientific article; zbMATH DE number 5703311