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Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network
This paper presents a hybrid control strategy, combining Radial Basis Function (RBF) network with conventional proportional, integral, and derivative (PID) controllers, for the greenhouse climate control. A model of nonlinear conservation laws of enthalpy and matter between numerous system variables...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3386686/ https://www.ncbi.nlm.nih.gov/pubmed/22778587 http://dx.doi.org/10.3390/s120505328 |
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author | Zeng, Songwei Hu, Haigen Xu, Lihong Li, Guanghui |
author_facet | Zeng, Songwei Hu, Haigen Xu, Lihong Li, Guanghui |
author_sort | Zeng, Songwei |
collection | PubMed |
description | This paper presents a hybrid control strategy, combining Radial Basis Function (RBF) network with conventional proportional, integral, and derivative (PID) controllers, for the greenhouse climate control. A model of nonlinear conservation laws of enthalpy and matter between numerous system variables affecting the greenhouse climate is formulated. RBF network is used to tune and identify all PID gain parameters online and adaptively. The presented Neuro-PID control scheme is validated through simulations of set-point tracking and disturbance rejection. We compare the proposed adaptive online tuning method with the offline tuning scheme that employs Genetic Algorithm (GA) to search the optimal gain parameters. The results show that the proposed strategy has good adaptability, strong robustness and real-time performance while achieving satisfactory control performance for the complex and nonlinear greenhouse climate control system, and it may provide a valuable reference to formulate environmental control strategies for actual application in greenhouse production. |
format | Online Article Text |
id | pubmed-3386686 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-33866862012-07-09 Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network Zeng, Songwei Hu, Haigen Xu, Lihong Li, Guanghui Sensors (Basel) Article This paper presents a hybrid control strategy, combining Radial Basis Function (RBF) network with conventional proportional, integral, and derivative (PID) controllers, for the greenhouse climate control. A model of nonlinear conservation laws of enthalpy and matter between numerous system variables affecting the greenhouse climate is formulated. RBF network is used to tune and identify all PID gain parameters online and adaptively. The presented Neuro-PID control scheme is validated through simulations of set-point tracking and disturbance rejection. We compare the proposed adaptive online tuning method with the offline tuning scheme that employs Genetic Algorithm (GA) to search the optimal gain parameters. The results show that the proposed strategy has good adaptability, strong robustness and real-time performance while achieving satisfactory control performance for the complex and nonlinear greenhouse climate control system, and it may provide a valuable reference to formulate environmental control strategies for actual application in greenhouse production. Molecular Diversity Preservation International (MDPI) 2012-04-26 /pmc/articles/PMC3386686/ /pubmed/22778587 http://dx.doi.org/10.3390/s120505328 Text en © 2012 by the authors; licensee MDPI, Basel, Switzerland This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Zeng, Songwei Hu, Haigen Xu, Lihong Li, Guanghui Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network |
title | Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network |
title_full | Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network |
title_fullStr | Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network |
title_full_unstemmed | Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network |
title_short | Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network |
title_sort | nonlinear adaptive pid control for greenhouse environment based on rbf network |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3386686/ https://www.ncbi.nlm.nih.gov/pubmed/22778587 http://dx.doi.org/10.3390/s120505328 |
work_keys_str_mv | AT zengsongwei nonlinearadaptivepidcontrolforgreenhouseenvironmentbasedonrbfnetwork AT huhaigen nonlinearadaptivepidcontrolforgreenhouseenvironmentbasedonrbfnetwork AT xulihong nonlinearadaptivepidcontrolforgreenhouseenvironmentbasedonrbfnetwork AT liguanghui nonlinearadaptivepidcontrolforgreenhouseenvironmentbasedonrbfnetwork |