Iterative learning control for nonlinear weighing and feeding process
type: Item
instance of: scholarly article
title: Iterative learning control for nonlinear weighing and feeding process
zbMATH Open document ID: 1427.93009
DOI: 10.1155/2018/9425902
author: Jianqi An
author: Fayang You
author: Min Wu
author: Jinhua She
published in: Mathematical Problems in Engineering
publication date: 2019-02-08T00:00:00Z
review text: Summary: Due to the nonlinear dynamics in weighing and feeding process, it is difficult to achieve high accuracy with conventional control methods. This paper uses a piecewise linearization method for the nonlinear problem and discusses the application of iterative learning control in weighing and feeding process. First, the nonlinear problem and the repeatability are discussed based on dynamic analysis of weighing and feeding process. Next, a linear state space model is established with a piecewise linearization method. Then, an iterative learning controller is presented by utilizing repetitive characteristics, and the controller parameters are obtained by using a multi-objective optimization method. Finally, simulation results show that the presented control method improves the control performances and the accuracy of feeding.
Mathematics Subject Classification ID: 93-08
Mathematics Subject Classification ID: 35Q74
Mathematics Subject Classification ID: 35J10
Mathematics Subject Classification ID: 93E15
zbMATH DE Number: 7019760
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2018/9425902
OpenAlex ID: W2904374674
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Wikidata QID: Q128778245
description: scientific article; zbMATH DE number 7019760