Feedback-assisted iterative learning model predictive control with nonlinear fuzzy model
type: Item
instance of: scholarly article
title: Feedback-assisted iterative learning model predictive control with nonlinear fuzzy model
zbMATH Open document ID: 1407.93440
DOI: 10.1155/2014/874705
author: Ke Xi
author: Xiangjie Liu
published in: Mathematical Problems in Engineering
publication date: 2019-02-08T00:00:00Z
review text: Summary: Iterative learning control (ILC), due to its advantage of requiring less system knowledge, can serve as a feedforward signal in system control. ILC can be combined with model predictive control (MPC) to constitute a feedforward-feedback configuration. In this scheme, ILC provides most of the control signal and copes with the repetitive disturbances. MPC provides the supplementary control for regulation purpose and also for nonrepeating disturbance rejection. Considering the nonlinear industrial process, this paper establishes the plant nonlinear fuzzy model to constitute the fuzzy model-based feedback-assisted ILC. The integrated control strategy can achieve wide-range operation and good tracking performance. The performance of the feedback-assisted ILC is illustrated by a steam-boiler system.
Mathematics Subject Classification ID: 93E35
Mathematics Subject Classification ID: 93C42
zbMATH DE Number: 7017503
Wikidata QID: Q59070344
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2014/874705
OpenAlex ID: W2101780467
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description: scientific article; zbMATH DE number 7017503