Robust identification of non-linear greenhouse model using evolutionary algorithms

This paper presents the non-linear modelling, based on first principle equations, for a climatic model of a greenhouse and the estimation of the feasible parameter set ( FPS) when the identification error is bounded simultaneously by several norms. The robust identification problem is transformed in...

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Bibliographic Details
Published in:Control engineering practice Vol. 16; no. 5; pp. 515 - 530
Main Authors: Herrero, J.M., Blasco, X., Martínez, M., Ramos, C., Sanchis, J.
Format: Journal Article
Language:English
Published: Oxford Elsevier Ltd 01.05.2008
Elsevier
Subjects:
Applied sciences
Computer science; control theory; systems
Control theory. Systems
Evolutionary algorithms
Exact sciences and technology
Greenhouse modelling
Modelling and identification
Multimodal optimization
Multiobjective optimization
Robust identification
Evolutionary algorithms
Multimodal optimization
Multiobjective optimization
Greenhouse modelling
Robust identification
Parameter estimation
Evolutionary algorithm
Bounded error
Multiobjective programming
Modeling
Optimization
Non linear model
System identification
Greenhouse
ISSN:0967-0661, 1873-6939
Online Access:Get full text
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Summary:This paper presents the non-linear modelling, based on first principle equations, for a climatic model of a greenhouse and the estimation of the feasible parameter set ( FPS) when the identification error is bounded simultaneously by several norms. The robust identification problem is transformed into a multimodal optimization problem with an infinite number of global minima that constitute the FPS. For the optimization task, a special evolutionary algorithm ( ε -GA) is presented, which characterizes the FPS by means of a discrete set of models that are well distributed along the FPS. A procedure for determining the norm bounds, such that FPS ≠ ∅ , is presented.
ISSN:0967-0661
1873-6939
DOI:10.1016/j.conengprac.2007.06.001