Composite learning sliding mode control of flexible-link manipulator
type: Item
instance of: scholarly article
title: Composite learning sliding mode control of flexible-link manipulator
zbMATH Open document ID: 1373.93083
DOI: 10.1155/2017/9430259
author: Bin Xu
author: Pengchao Zhang
published in: Complexity
publication date: 2017-10-26T00:00:00Z
review text: Summary: This paper studies the control of a flexible-link manipulator with uncertainty. The fast and slow dynamics are derived based on the singular perturbation (SP) theory. The sliding mode control is proposed while the adaptive design is developed using Neural Networks (NNs) and Disturbance OBserver (DOB) where the novel update laws for NN and DOB are designed. The closed-loop system stability is guaranteed via Lyapunov analysis. The effectiveness of the proposed method is verified via simulation test.
Mathematics Subject Classification ID: 93B12
Mathematics Subject Classification ID: 93C70
Mathematics Subject Classification ID: 93C85
Mathematics Subject Classification ID: 93D05
zbMATH DE Number: 6798536
zbMATH Keywords: composite learning sliding mode control
zbMATH Keywords: flexible-link manipulator
zbMATH Keywords: uncertainty
zbMATH Keywords: singular perturbation (SP) theory
zbMATH Keywords: adaptive design
zbMATH Keywords: neural networks (NNs)
zbMATH Keywords: disturbance observer (DOB)
zbMATH Keywords: closed-loop system stability
zbMATH Keywords: Lyapunov analysis
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2017/9430259
OpenAlex ID: W2742423417
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description: scientific article; zbMATH DE number 6798536