RBF-ARX model-based robust MPC for nonlinear systems with unknown and bounded disturbance
type: Item
instance of: scholarly article
title: RBF-ARX model-based robust MPC for nonlinear systems with unknown and bounded disturbance
zbMATH Open document ID: 1380.93113
author: Feng Zhou
author: Hui Peng
author: Xiaoyong Zeng
author: Xiaoying Tian
author: Xiaoyan Peng
published in: Journal of the Franklin Institute
publication date: 2018-02-05T00:00:00Z
Mathematics Subject Classification ID: 93B40
Mathematics Subject Classification ID: 93B35
Mathematics Subject Classification ID: 93E25
Mathematics Subject Classification ID: 93C10
Mathematics Subject Classification ID: 93C41
zbMATH DE Number: 6834037
zbMATH Keywords: RBF-ARX model-based robust predictive control
zbMATH Keywords: output tracking control
zbMATH Keywords: nonlinear system
zbMATH Keywords: polytopic uncertain linear parameter varying (LPV) state-space model
zbMATH Keywords: quasi-min-max robust MPC algorithm
zbMATH Keywords: stability
zbMATH Keywords: parameter-dependent Lyapunov function
zbMATH Keywords: continuously stirred tank reactor (CSTR) simulator
MaRDI profile type: Publication
full work available at URL: j.jfranklin.2017.10.002
OpenAlex ID: W2765092711
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DOI: 10.1016/J.JFRANKLIN.2017.10.002
description: scientific article; zbMATH DE number 6834037