Identificación basada en redes neuronales artificiales de un tramo de un canal principal de riego (Artificial Neural Network Based System Identification of an Irrigation Main Canal Pool)

Ybrain Hernández López (ybra@automatica.cujae.edu.cu)2, Vicente Feliu Batlle (vicente.feliu@uclm.es)1, Raúl Rivas Perez (rivas@automatica.cujae.edu.cu)2


1Universidad de Castilla La Mancha
2Universidad Tecnológica de la Habana, CUJAE

This paper appears in: Revista IEEE América Latina

Publication Date: Sept. 2017
Volume: 15,   Issue: 9 
ISSN: 1548-0992


Abstract:
In this paper by applying system identification tools a neural network model of an irrigation main canal pool is obtained. The complete system identification procedure, from experimental design to model validation, taking into account prior physical information, is developed. It is established that a nonlinear model with NARX structure can adequately describe the dynamic behavior of an irrigation main canal pool. The model validation results show that the model obtained reproduces with high accuracy the observed data and therefore it can be applied in the design of nonlinear control systems and/or for prediction purposes.

Index Terms:
System identification, artificial neural network, irrigation main canal pool, management of water resources, irrigation system automation   


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