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A Two-Time Scale Decentralized Model Predictive Controller Based on Input and Output Model
A decentralized model predictive controller applicable for some systems which exhibit different dynamic characteristics in different channels was presented in this paper. These systems can be regarded as combinations of a fast model and a slow model, the response speeds of which are in two-time scal...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2756468/ https://www.ncbi.nlm.nih.gov/pubmed/19834542 http://dx.doi.org/10.1155/2009/164568 |
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author | Niu, Jian Zhao, Jun Xu, Zuhua Qian, Jixin |
author_facet | Niu, Jian Zhao, Jun Xu, Zuhua Qian, Jixin |
author_sort | Niu, Jian |
collection | PubMed |
description | A decentralized model predictive controller applicable for some systems which exhibit different dynamic characteristics in different channels was presented in this paper. These systems can be regarded as combinations of a fast model and a slow model, the response speeds of which are in two-time scale. Because most practical models used for control are obtained in the form of transfer function matrix by plant tests, a singular perturbation method was firstly used to separate the original transfer function matrix into two models in two-time scale. Then a decentralized model predictive controller was designed based on the two models derived from the original system. And the stability of the control method was proved. Simulations showed that the method was effective. |
format | Text |
id | pubmed-2756468 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-27564682009-10-15 A Two-Time Scale Decentralized Model Predictive Controller Based on Input and Output Model Niu, Jian Zhao, Jun Xu, Zuhua Qian, Jixin J Autom Methods Manag Chem Research Article A decentralized model predictive controller applicable for some systems which exhibit different dynamic characteristics in different channels was presented in this paper. These systems can be regarded as combinations of a fast model and a slow model, the response speeds of which are in two-time scale. Because most practical models used for control are obtained in the form of transfer function matrix by plant tests, a singular perturbation method was firstly used to separate the original transfer function matrix into two models in two-time scale. Then a decentralized model predictive controller was designed based on the two models derived from the original system. And the stability of the control method was proved. Simulations showed that the method was effective. Hindawi Publishing Corporation 2009 2009-09-30 /pmc/articles/PMC2756468/ /pubmed/19834542 http://dx.doi.org/10.1155/2009/164568 Text en Copyright © 2009 Jian Niu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Niu, Jian Zhao, Jun Xu, Zuhua Qian, Jixin A Two-Time Scale Decentralized Model Predictive Controller Based on Input and Output Model |
title | A Two-Time Scale Decentralized Model Predictive Controller Based on Input and Output Model |
title_full | A Two-Time Scale Decentralized Model Predictive Controller Based on Input and Output Model |
title_fullStr | A Two-Time Scale Decentralized Model Predictive Controller Based on Input and Output Model |
title_full_unstemmed | A Two-Time Scale Decentralized Model Predictive Controller Based on Input and Output Model |
title_short | A Two-Time Scale Decentralized Model Predictive Controller Based on Input and Output Model |
title_sort | two-time scale decentralized model predictive controller based on input and output model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2756468/ https://www.ncbi.nlm.nih.gov/pubmed/19834542 http://dx.doi.org/10.1155/2009/164568 |
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